Entry script:
https://github.com/utensil/llm-playground/blob/main/scripts/entry/ax_lite.sh
Mount volume disk to /content
Save to:
utensil/llm-playground
notebooks/axolotl/runpod/axolotl-falcon-40b-qlora-deepspeed.ipynb
!pip install git+https://github.com/cphyc/jupyter-notify.git
Collecting git+https://github.com/cphyc/jupyter-notify.git Cloning https://github.com/cphyc/jupyter-notify.git to /tmp/pip-req-build-zu3hp4aa Running command git clone --filter=blob:none --quiet https://github.com/cphyc/jupyter-notify.git /tmp/pip-req-build-zu3hp4aa Resolved https://github.com/cphyc/jupyter-notify.git to commit 8cff958cbd3f00f7e4eb59b457f9f915e2ddff37 Preparing metadata (setup.py) ... done Requirement already satisfied: ipython in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from jupyternotify==0.1.15) (8.14.0) Requirement already satisfied: jupyter in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from jupyternotify==0.1.15) (1.0.0) Requirement already satisfied: backcall in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from ipython->jupyternotify==0.1.15) (0.2.0) Requirement already satisfied: decorator in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from ipython->jupyternotify==0.1.15) (5.1.1) Requirement already 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/root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from ipython->jupyternotify==0.1.15) (5.9.0) Requirement already satisfied: typing-extensions in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from ipython->jupyternotify==0.1.15) (4.6.3) Requirement already satisfied: pexpect>4.3 in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from ipython->jupyternotify==0.1.15) (4.8.0) Requirement already satisfied: notebook in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from jupyter->jupyternotify==0.1.15) (6.5.4) Requirement already satisfied: qtconsole in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from jupyter->jupyternotify==0.1.15) (5.4.3) Requirement already satisfied: jupyter-console in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from jupyter->jupyternotify==0.1.15) (6.6.3) Requirement already satisfied: nbconvert in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from jupyter->jupyternotify==0.1.15) (7.5.0) Requirement already satisfied: ipykernel in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from jupyter->jupyternotify==0.1.15) (6.23.2) Requirement already satisfied: ipywidgets in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from jupyter->jupyternotify==0.1.15) (8.0.6) Requirement already satisfied: parso<0.9.0,>=0.8.0 in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from jedi>=0.16->ipython->jupyternotify==0.1.15) (0.8.3) Requirement already satisfied: ptyprocess>=0.5 in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from pexpect>4.3->ipython->jupyternotify==0.1.15) (0.7.0) Requirement already satisfied: wcwidth in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from prompt-toolkit!=3.0.37,<3.1.0,>=3.0.30->ipython->jupyternotify==0.1.15) (0.2.6) Requirement already satisfied: comm>=0.1.1 in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from ipykernel->jupyter->jupyternotify==0.1.15) (0.1.3) Requirement already satisfied: debugpy>=1.6.5 in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from ipykernel->jupyter->jupyternotify==0.1.15) (1.6.7) Requirement already satisfied: jupyter-client>=6.1.12 in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from ipykernel->jupyter->jupyternotify==0.1.15) (8.2.0) Requirement already satisfied: jupyter-core!=5.0.*,>=4.12 in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from ipykernel->jupyter->jupyternotify==0.1.15) (5.3.1) Requirement already satisfied: nest-asyncio in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from ipykernel->jupyter->jupyternotify==0.1.15) (1.5.6) Requirement already satisfied: packaging in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from ipykernel->jupyter->jupyternotify==0.1.15) (23.1) Requirement already satisfied: psutil in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from ipykernel->jupyter->jupyternotify==0.1.15) (5.9.5) Requirement already satisfied: pyzmq>=20 in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from ipykernel->jupyter->jupyternotify==0.1.15) (25.1.0) Requirement already satisfied: tornado>=6.1 in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from ipykernel->jupyter->jupyternotify==0.1.15) (6.3.2) Requirement already satisfied: widgetsnbextension~=4.0.7 in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from ipywidgets->jupyter->jupyternotify==0.1.15) (4.0.7) Requirement already satisfied: jupyterlab-widgets~=3.0.7 in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from ipywidgets->jupyter->jupyternotify==0.1.15) (3.0.7) Requirement already satisfied: beautifulsoup4 in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from nbconvert->jupyter->jupyternotify==0.1.15) (4.12.2) Requirement already satisfied: bleach!=5.0.0 in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from nbconvert->jupyter->jupyternotify==0.1.15) (6.0.0) Requirement already satisfied: defusedxml in 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satisfied: isoduration in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from jsonschema>=2.6->nbformat>=5.7->nbconvert->jupyter->jupyternotify==0.1.15) (20.11.0) Requirement already satisfied: jsonpointer>1.13 in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from jsonschema>=2.6->nbformat>=5.7->nbconvert->jupyter->jupyternotify==0.1.15) (2.3) Requirement already satisfied: uri-template in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from jsonschema>=2.6->nbformat>=5.7->nbconvert->jupyter->jupyternotify==0.1.15) (1.2.0) Requirement already satisfied: webcolors>=1.11 in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from jsonschema>=2.6->nbformat>=5.7->nbconvert->jupyter->jupyternotify==0.1.15) (1.13) Requirement already satisfied: arrow>=0.15.0 in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from isoduration->jsonschema>=2.6->nbformat>=5.7->nbconvert->jupyter->jupyternotify==0.1.15) (1.2.3) WARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv
%load_ext jupyternotify
%autonotify -a 30 -o
# %env HF_DATASETS_CACHE
#%env TRANSFORMERS_CACHE
!rm -rf /root/.cache
!mkdir -p /content/cache
!ln -s /content/cache /root/.cache
!apt-get update
!apt-get install -y aria2
!git lfs install
!pip install requests huggingface_hub
Hit:1 http://archive.ubuntu.com/ubuntu jammy InRelease Get:2 http://security.ubuntu.com/ubuntu jammy-security InRelease [110 kB] Get:3 http://archive.ubuntu.com/ubuntu jammy-updates InRelease [119 kB] Hit:4 https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64 InRelease Get:5 http://archive.ubuntu.com/ubuntu jammy-backports InRelease [108 kB] Get:6 http://archive.ubuntu.com/ubuntu jammy-updates/universe amd64 Packages [1185 kB] Get:7 http://archive.ubuntu.com/ubuntu jammy-updates/main amd64 Packages [919 kB] Get:8 http://archive.ubuntu.com/ubuntu jammy-updates/restricted amd64 Packages [545 kB] Fetched 2985 kB in 1s (3189 kB/s) Reading package lists... Done Reading package lists... Done Building dependency tree... Done Reading state information... Done The following additional packages will be installed: libaria2-0 libc-ares2 libicu70 libssh2-1 libxml2 The following NEW packages will be installed: aria2 libaria2-0 libc-ares2 libicu70 libssh2-1 libxml2 0 upgraded, 6 newly installed, 0 to remove and 58 not upgraded. Need to get 13.0 MB of archives. After this operation, 43.2 MB of additional disk space will be used. Get:1 http://archive.ubuntu.com/ubuntu jammy/main amd64 libicu70 amd64 70.1-2 [10.6 MB] Get:2 http://archive.ubuntu.com/ubuntu jammy-updates/main amd64 libxml2 amd64 2.9.13+dfsg-1ubuntu0.3 [763 kB] Get:3 http://archive.ubuntu.com/ubuntu jammy-updates/main amd64 libc-ares2 amd64 1.18.1-1ubuntu0.22.04.2 [45.0 kB] Get:4 http://archive.ubuntu.com/ubuntu jammy/universe amd64 libssh2-1 amd64 1.10.0-3 [109 kB] Get:5 http://archive.ubuntu.com/ubuntu jammy/universe amd64 libaria2-0 amd64 1.36.0-1 [1086 kB] Get:6 http://archive.ubuntu.com/ubuntu jammy/universe amd64 aria2 amd64 1.36.0-1 [381 kB] Fetched 13.0 MB in 2s (8370 kB/s) debconf: delaying package configuration, since apt-utils is not installed Selecting previously unselected package libicu70:amd64. (Reading database ... 17816 files and directories currently installed.) Preparing to unpack .../0-libicu70_70.1-2_amd64.deb ... Unpacking libicu70:amd64 (70.1-2) ... Selecting previously unselected package libxml2:amd64. 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Setting up aria2 (1.36.0-1) ... Processing triggers for libc-bin (2.35-0ubuntu3.1) ... Updated git hooks. Git LFS initialized. Requirement already satisfied: requests in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (2.31.0) Requirement already satisfied: huggingface_hub in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (0.15.1) Requirement already satisfied: charset-normalizer<4,>=2 in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from requests) (3.1.0) Requirement already satisfied: idna<4,>=2.5 in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from requests) (3.4) Requirement already satisfied: urllib3<3,>=1.21.1 in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from requests) (2.0.3) Requirement already satisfied: certifi>=2017.4.17 in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from requests) (2023.5.7) Requirement already satisfied: filelock in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from huggingface_hub) (3.12.2) Requirement already satisfied: fsspec in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from huggingface_hub) (2023.6.0) Requirement already satisfied: tqdm>=4.42.1 in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from huggingface_hub) (4.65.0) Requirement already satisfied: pyyaml>=5.1 in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from huggingface_hub) (6.0) Requirement already satisfied: typing-extensions>=3.7.4.3 in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from huggingface_hub) (4.6.3) Requirement already satisfied: packaging>=20.9 in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from huggingface_hub) (23.1) WARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv
#%cd /content/
#!git clone https://github.com/utensil/llm-playground
%cd /content/llm-playground
/content/llm-playground
!python /content/llm-playground/helper/download-model.py tiiuae/falcon-40b
# /content/llm-playground/models/tiiuae_falcon-40b
Working directory changed to: /content/llm-playground/helper/.. Skipping: .gitattributes Downloading the model to models/tiiuae_falcon-40b Running: aria2c -c -x 16 -s 16 -k 1M https://huggingface.co/tiiuae/falcon-40b/resolve/main/README.md -d models/tiiuae_falcon-40b -o README.md Running: aria2c -c -x 16 -s 16 -k 1M https://huggingface.co/tiiuae/falcon-40b/resolve/main/config.json -d models/tiiuae_falcon-40b -o config.json Running: aria2c -c -x 16 -s 16 -k 1M https://huggingface.co/tiiuae/falcon-40b/resolve/main/configuration_RW.py -d models/tiiuae_falcon-40b -o configuration_RW.py Running: aria2c -c -x 16 -s 16 -k 1M https://huggingface.co/tiiuae/falcon-40b/resolve/main/generation_config.json -d models/tiiuae_falcon-40b -o generation_config.json Running: aria2c -c -x 16 -s 16 -k 1M https://huggingface.co/tiiuae/falcon-40b/resolve/main/modelling_RW.py -d models/tiiuae_falcon-40b -o modelling_RW.py 06/16 05:46:00 [NOTICE] Downloading 1 item(s) Running: aria2c -c -x 16 -s 16 -k 1M https://huggingface.co/tiiuae/falcon-40b/resolve/main/pytorch_model-00001-of-00009.bin -d models/tiiuae_falcon-40b -o pytorch_model-00001-of-00009.bin 06/16 05:46:00 [NOTICE] Downloading 1 item(s) 06/16 05:46:00 [NOTICE] Downloading 1 item(s) Running: aria2c -c -x 16 -s 16 -k 1M https://huggingface.co/tiiuae/falcon-40b/resolve/main/pytorch_model-00002-of-00009.bin -d models/tiiuae_falcon-40b -o pytorch_model-00002-of-00009.bin 06/16 05:46:00 [NOTICE] Downloading 1 item(s) Running: aria2c -c -x 16 -s 16 -k 1M https://huggingface.co/tiiuae/falcon-40b/resolve/main/pytorch_model-00003-of-00009.bin -d models/tiiuae_falcon-40b -o pytorch_model-00003-of-00009.bin 0%| | 0/18 [00:00<?, ?it/s] 06/16 05:46:00 [NOTICE] Downloading 1 item(s) 06/16 05:46:00 [NOTICE] Downloading 1 item(s) 06/16 05:46:00 [NOTICE] Downloading 1 item(s) 06/16 05:46:00 [NOTICE] Downloading 1 item(s) 06/16 05:46:00 [NOTICE] Download complete: models/tiiuae_falcon-40b/configuration_RW.py Download Results: gid |stat|avg speed |path/URI ======+====+===========+======================================================= 0d4633|OK | n/a|models/tiiuae_falcon-40b/configuration_RW.py Status Legend: (OK):download completed. 06/16 05:46:00 [NOTICE] Download complete: models/tiiuae_falcon-40b/config.json Download Results: gid |stat|avg speed |path/URI ======+====+===========+======================================================= 1e2c93|OK | n/a|models/tiiuae_falcon-40b/config.json Status Legend: (OK):download completed. Running: aria2c -c -x 16 -s 16 -k 1M https://huggingface.co/tiiuae/falcon-40b/resolve/main/pytorch_model-00004-of-00009.bin -d models/tiiuae_falcon-40b -o pytorch_model-00004-of-00009.bin 06/16 05:46:00 [NOTICE] Download complete: models/tiiuae_falcon-40b/generation_config.json Download Results: gid |stat|avg speed |path/URI ======+====+===========+======================================================= 0072bb|OK | n/a|models/tiiuae_falcon-40b/generation_config.json Status Legend: (OK):download completed. Running: aria2c -c -x 16 -s 16 -k 1M https://huggingface.co/tiiuae/falcon-40b/resolve/main/pytorch_model-00005-of-00009.bin -d models/tiiuae_falcon-40b -o pytorch_model-00005-of-00009.bin Running: aria2c -c -x 16 -s 16 -k 1M https://huggingface.co/tiiuae/falcon-40b/resolve/main/pytorch_model-00006-of-00009.bin -d models/tiiuae_falcon-40b -o pytorch_model-00006-of-00009.bin 06/16 05:46:00 [NOTICE] CUID#7 - Redirecting to https://cdn-lfs.huggingface.co/repos/a3/72/a37288fd25de45b6a8bbb79801907289f6c12bb870db68f75b0024193da1f047/b2125ceee3992a093f9808efc9a720643a44e59b17baa77eddb0fbec6965ce5a?response-content-disposition=attachment%3B+filename*%3DUTF-8%27%27pytorch_model-00003-of-00009.bin%3B+filename%3D%22pytorch_model-00003-of-00009.bin%22%3B&response-content-type=application%2Foctet-stream&Expires=1687153231&Policy=eyJTdGF0ZW1lbnQiOlt7IlJlc291cmNlIjoiaHR0cHM6Ly9jZG4tbGZzLmh1Z2dpbmdmYWNlLmNvL3JlcG9zL2EzLzcyL2EzNzI4OGZkMjVkZTQ1YjZhOGJiYjc5ODAxOTA3Mjg5ZjZjMTJiYjg3MGRiNjhmNzViMDAyNDE5M2RhMWYwNDcvYjIxMjVjZWVlMzk5MmEwOTNmOTgwOGVmYzlhNzIwNjQzYTQ0ZTU5YjE3YmFhNzdlZGRiMGZiZWM2OTY1Y2U1YT9yZXNwb25zZS1jb250ZW50LWRpc3Bvc2l0aW9uPSomcmVzcG9uc2UtY29udGVudC10eXBlPSoiLCJDb25kaXRpb24iOnsiRGF0ZUxlc3NUaGFuIjp7IkFXUzpFcG9jaFRpbWUiOjE2ODcxNTMyMzF9fX1dfQ__&Signature=zq6%7EQqPrJV3VrXo4T9TbcecaeSYQR8UtAxm6%7EOQuxZp4gg4SUwMGQyBTucihhYS8tT9MtN0GHLbVgh7Mn62BpTs5q4z0wx9bsg1Btr624rsr937P5a9hWlwqXi3APOh9wnGEINK5liH-Jv1W69wDWoCLHX04FiXYLt50AqPWR4JQ8VUPacshFEsrDM1F85wVl77IadH%7EmvyWMTYJ%7ErCSxdz4q2-hWeC7gMPTUf43Wo6mzSJisVpkTX6nrsGMTWcvr%7EU4z-euMbGgnf-IsJGWeYhIL9WglLYXBgfo7HedX6IiVPx5xMcVgrOaRPs%7EbbNq6Cd7RUa6pf%7E02xdaX4dGDg__&Key-Pair-Id=KVTP0A1DKRTAX 06/16 05:46:00 [NOTICE] Downloading 1 item(s) 06/16 05:46:00 [NOTICE] Downloading 1 item(s) 06/16 05:46:00 [NOTICE] Downloading 1 item(s) 06/16 05:46:00 [NOTICE] Download complete: models/tiiuae_falcon-40b/modelling_RW.py Download Results: gid |stat|avg speed |path/URI ======+====+===========+======================================================= 44c44b|OK | 1.3MiB/s|models/tiiuae_falcon-40b/modelling_RW.py Status Legend: (OK):download completed. Running: aria2c -c -x 16 -s 16 -k 1M https://huggingface.co/tiiuae/falcon-40b/resolve/main/pytorch_model-00007-of-00009.bin -d models/tiiuae_falcon-40b -o pytorch_model-00007-of-00009.bin 06/16 05:46:00 [NOTICE] Downloading 1 item(s) 06/16 05:46:01 [NOTICE] CUID#7 - Redirecting to https://cdn-lfs.huggingface.co/repos/a3/72/a37288fd25de45b6a8bbb79801907289f6c12bb870db68f75b0024193da1f047/384bd92e6d1d0b6a133b1d81bad915a10d954d1bfcdf4fdc8b6d0d81b4f5e9e8?response-content-disposition=attachment%3B+filename*%3DUTF-8%27%27pytorch_model-00001-of-00009.bin%3B+filename%3D%22pytorch_model-00001-of-00009.bin%22%3B&response-content-type=application%2Foctet-stream&Expires=1687153561&Policy=eyJTdGF0ZW1lbnQiOlt7IlJlc291cmNlIjoiaHR0cHM6Ly9jZG4tbGZzLmh1Z2dpbmdmYWNlLmNvL3JlcG9zL2EzLzcyL2EzNzI4OGZkMjVkZTQ1YjZhOGJiYjc5ODAxOTA3Mjg5ZjZjMTJiYjg3MGRiNjhmNzViMDAyNDE5M2RhMWYwNDcvMzg0YmQ5MmU2ZDFkMGI2YTEzM2IxZDgxYmFkOTE1YTEwZDk1NGQxYmZjZGY0ZmRjOGI2ZDBkODFiNGY1ZTllOD9yZXNwb25zZS1jb250ZW50LWRpc3Bvc2l0aW9uPSomcmVzcG9uc2UtY29udGVudC10eXBlPSoiLCJDb25kaXRpb24iOnsiRGF0ZUxlc3NUaGFuIjp7IkFXUzpFcG9jaFRpbWUiOjE2ODcxNTM1NjF9fX1dfQ__&Signature=iNaCCN6qnYFUxwnxQeaAeD2SIvmH6QQU3oSUMU3ooPseaimTNN3Igpx1aeYQYHjAW5qvItarVqk5JoiEOfHkumJZgm3-OiKcbQPc7SXMnHA7Z6ItKrvN82N2l363JIGLpuPgfW1cSyqPRhHRTIu-h2RAKuCM6RI-VZz6904k5IQhat3GtF4H2JKlPZ-tL1Jn9z6TPH4ebt7hXY56opM2MsAk%7EdiE84luPziZv73vYL5ImQwroT2ctd35LuPXC82zo%7EZVBWpwFoDE3Wf3ofq8QMdCL%7E5PTgSby58IliJugvr9pTF9zjT8OGWnzbJo20jx2qaeseMLhrziyBP0Y5zntA__&Key-Pair-Id=KVTP0A1DKRTAX 06/16 05:46:01 [NOTICE] CUID#7 - 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# For axolotl push_dataset_to_hub
import os
from huggingface_hub import notebook_login, login
# Colab:
# notebook_login()
# RunPod:
login(os.environ.get("HUGGINGFACE_TOKEN"), add_to_git_credential=True)
Token is valid (permission: write). Your token has been saved in your configured git credential helpers (store). Your token has been saved to /root/.cache/huggingface/token Login successful
%cd /workspace/
!git clone https://github.com/OpenAccess-AI-Collective/axolotl axolotl-update
!cp -r axolotl-update/* axolotl
%cd /workspace/axolotl
!git status
!ds_report
!pip install -e .
!pip list|grep torch
!python /content/llm-playground/helper/storage.py utensil/axolotl-trained /content/ -m
/content/axolotl-trained is already a clone of https://huggingface.co/utensil/axolotl-trained. Make sure you pull the latest changes with `repo.git_pull()`.
!ls /content/axolotl-trained
falcon-qlora-40b-gsm8k
!pip3 install -U torch --index-url https://download.pytorch.org/whl/cu118
Looking in indexes: https://download.pytorch.org/whl/cu118 Requirement already satisfied: torch in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (2.0.1) Collecting torch Using cached https://download.pytorch.org/whl/cu118/torch-2.0.1%2Bcu118-cp39-cp39-linux_x86_64.whl (2267.3 MB) Requirement already satisfied: filelock in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from torch) (3.12.2) Requirement already satisfied: typing-extensions in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from torch) (4.6.3) Requirement already satisfied: sympy in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from torch) (1.12) Requirement already satisfied: networkx in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from torch) (3.1) Requirement already satisfied: jinja2 in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from torch) (3.1.2) Requirement already satisfied: triton==2.0.0 in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from torch) (2.0.0) Requirement already satisfied: cmake in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from triton==2.0.0->torch) (3.26.4) Requirement already satisfied: lit in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from triton==2.0.0->torch) (16.0.6) Requirement already satisfied: MarkupSafe>=2.0 in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from jinja2->torch) (2.1.3) Requirement already satisfied: mpmath>=0.19 in /root/miniconda3/envs/py3.9/lib/python3.9/site-packages (from sympy->torch) (1.3.0) Installing collected packages: torch Attempting uninstall: torch Found existing installation: torch 2.0.1 Uninstalling torch-2.0.1: Successfully uninstalled torch-2.0.1 ERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts. torchaudio 2.0.1+cu118 requires torch==2.0.0, but you have torch 2.0.1+cu118 which is incompatible. Successfully installed torch-2.0.1+cu118 WARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv
!pip list|grep torch
torch 2.0.1+cu118 torchaudio 2.0.1+cu118 torchvision 0.15.2
!ds_report
Setting ds_accelerator to cuda (auto detect) -------------------------------------------------- DeepSpeed C++/CUDA extension op report -------------------------------------------------- NOTE: Ops not installed will be just-in-time (JIT) compiled at runtime if needed. Op compatibility means that your system meet the required dependencies to JIT install the op. -------------------------------------------------- JIT compiled ops requires ninja ninja .................. [OKAY] -------------------------------------------------- op name ................ installed .. compatible -------------------------------------------------- async_io ............... [YES] ...... [OKAY] cpu_adagrad ............ [YES] ...... [OKAY] cpu_adam ............... [YES] ...... [OKAY] fused_adam ............. [YES] ...... [OKAY] fused_lamb ............. [YES] ...... [OKAY] quantizer .............. [YES] ...... [OKAY] random_ltd ............. [YES] ...... [OKAY] [WARNING] sparse_attn requires a torch version >= 1.5 and < 2.0 but detected 2.0 [WARNING] using untested triton version (2.0.0), only 1.0.0 is known to be compatible sparse_attn ............ [NO] ....... [NO] spatial_inference ...... [YES] ...... [OKAY] transformer ............ [YES] ...... [OKAY] stochastic_transformer . [YES] ...... [OKAY] transformer_inference .. [YES] ...... [OKAY] utils .................. [YES] ...... [OKAY] -------------------------------------------------- DeepSpeed general environment info: torch install path ............... ['/root/miniconda3/envs/py3.9/lib/python3.9/site-packages/torch'] torch version .................... 2.0.1+cu118 deepspeed install path ........... ['/root/miniconda3/envs/py3.9/lib/python3.9/site-packages/deepspeed'] deepspeed info ................... 0.9.3+52907a66, 52907a66, master torch cuda version ............... 11.8 torch hip version ................ None nvcc version ..................... 11.8 deepspeed wheel compiled w. ...... torch 2.0, cuda 11.8
# !yes|pip uninstall deepspeed
# !TORCH_CUDA_ARCH_LIST="3.5;5.0;6.0;6.1;7.0;7.5;8.0;8.6+PTX" DS_BUILD_OPS=1 DS_BUILD_SPARSE_ATTN=0 pip install deepspeed --global-option="build_ext" --global-option="-j8" # --global-option="bdist_wheel"
# !pip install deepspeed
# !ds_report
%cd /workspace/axolotl
/workspace/axolotl
# Try no config
# !accelerate config default
%%writefile ds_config.json
{
"zero_optimization": {
"stage": 3,
"offload_optimizer": {
"device": "cpu",
"pin_memory": true
},
"offload_param": {
"device": "cpu",
"pin_memory": true
},
"overlap_comm": true,
"contiguous_gradients": true,
"sub_group_size": 0,
"reduce_bucket_size": "auto",
"stage3_prefetch_bucket_size": "auto",
"stage3_param_persistence_threshold": "auto",
"stage3_max_live_parameters": 0,
"stage3_max_reuse_distance": 0,
"stage3_gather_16bit_weights_on_model_save": true
},
"bf16": {
"enabled": "auto"
},
"fp16": {
"enabled": "auto",
"auto_cast": false,
"loss_scale": 0,
"initial_scale_power": 32,
"loss_scale_window": 1000,
"hysteresis": 2,
"min_loss_scale": 1
},
"optimizer": {
"type": "AdamW",
"params": {
"lr": "auto",
"betas": "auto",
"eps": "auto",
"weight_decay": "auto"
}
},
"scheduler": {
"type": "WarmupDecayLR",
"params": {
"total_num_steps": "auto",
"warmup_min_lr": "auto",
"warmup_max_lr": "auto",
"warmup_num_steps": "auto"
}
},
"gradient_accumulation_steps": "auto",
"train_batch_size": "auto",
"train_micro_batch_size_per_gpu": "auto",
"wall_clock_breakdown": false
}
Overwriting ds_config.json
%%writefile examples/falcon/config-40b-qlora.yml
# 1b: tiiuae/falcon-rw-1b
# 7b: tiiuae/falcon-7b
# 40b: tiiuae/falcon-40b
base_model: /content/llm-playground/models/tiiuae_falcon-40b
base_model_config: /content/llm-playground/models/tiiuae_falcon-40b
# required by falcon custom model code: https://huggingface.co/tiiuae/falcon-7b/tree/main
trust_remote_code: true
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer
load_in_8bit: false
# enable 4bit for QLoRA
load_in_4bit: true
gptq: false
strict: false
push_dataset_to_hub: utensil
hf_use_auth_token: true
datasets:
- path: winglian/evals
data_files:
- hf/ARC-Challenge.jsonl
- hf/ARC-Easy.jsonl
- hf/riddle_sense.jsonl
type: explainchoice:chat
- path: winglian/evals
data_files:
- hf/gsm8k.jsonl
- hf/winogrande.jsonl
type: alpaca_chat.load_qa
- path: winglian/evals
data_files:
- custom/n_task.jsonl
- custom/misconceptions.jsonl
- custom/context_insensitivity.jsonl
type: alpaca_chat
- path: camel-ai/math
type: alpaca_chat.load_camel_ai
- path: camel-ai/biology
type: alpaca_chat.load_camel_ai
- path: camel-ai/physics
type: alpaca_chat.load_camel_ai
- path: camel-ai/chemistry
type: alpaca_chat.load_camel_ai
- path: winglian/evals
data_files:
- custom/in_context_qa.jsonl
type: context_qa
- path: winglian/evals
data_files:
- custom/in_context_qa.jsonl
type: context_qa.load_404
- path: winglian/evals
data_files:
- custom/jokes_explained_500up.jsonl
type: sharegpt_jokes
- path: winglian/evals
data_files:
- custom/classify-self-chat.sharegpt.jsonl
- custom/coding-self-chat.sharegpt.jsonl
- custom/prose-gpt4.sharegpt.jsonl
- custom/prose-rewrite-gpt4.sharegpt.jsonl
type: sharegpt_simple.load_role
- path: winglian/evals
data_files:
- openai/tldr.jsonl
type: summarizetldr:chat
- path: winglian/evals
data_files:
- hellaswag/hellaswag.jsonl
type: explainchoice:chat
- path: metaeval/ScienceQA_text_only
type: concisechoice:chat
- path: teknium/GPT4-LLM-Cleaned
type: alpaca_chat
- path: teknium/GPTeacher-General-Instruct
data_files: gpt4-instruct-similarity-0.6-dataset.json
type: gpteacher:chat
- path: QingyiSi/Alpaca-CoT
data_files:
- Chain-of-Thought/formatted_cot_data/aqua_train.json
- Chain-of-Thought/formatted_cot_data/creak_train.json
- Chain-of-Thought/formatted_cot_data/ecqa_train.json
- Chain-of-Thought/formatted_cot_data/esnli_train.json
- Chain-of-Thought/formatted_cot_data/qasc_train.json
- Chain-of-Thought/formatted_cot_data/qed_train.json
- Chain-of-Thought/formatted_cot_data/sensemaking_train.json
- Chain-of-Thought/formatted_cot_data/strategyqa_train.json
- GPTeacher/Roleplay/formatted_roleplay-similarity_0.6-instruct-dataset.json
type: alpaca_chat
- path: ehartford/WizardLM_alpaca_evol_instruct_70k_unfiltered
type: alpaca_chat
- path: ehartford/wizard_vicuna_70k_unfiltered
type: sharegpt:chat
dataset_prepared_path: last_run_prepared
val_set_size: 0.01
# enable QLoRA
adapter: qlora
lora_model_dir:
sequence_len: 2048
max_packed_sequence_len: 2048
# hyperparameters from QLoRA paper Appendix B.2
# "We find hyperparameters to be largely robust across datasets"
lora_r: 64
lora_alpha: 16
# 0.1 for models up to 13B
# 0.05 for 33B and 65B models
lora_dropout: 0.05
# add LoRA modules on all linear layers of the base model
lora_target_modules:
lora_target_linear: true
lora_fan_in_fan_out:
wandb_project: falcon-qlora
wandb_watch:
wandb_run_id:
wandb_log_model:
output_dir: /content/axolotl-trained/falcon-qlora-40b-minotaur/
# QLoRA paper Table 9
# - 16 for 7b & 13b
# - 32 for 33b, 64 for 64b
# Max size tested on A6000
# - 7b: 40
# - 40b: 4
# decrease if OOM, increase for max VRAM utilization
micro_batch_size: 4
gradient_accumulation_steps: 1
num_epochs: 3
# Optimizer for QLoRA
optimizer: paged_adamw_32bit
torchdistx_path:
lr_scheduler: cosine
# QLoRA paper Table 9
# - 2e-4 for 7b & 13b
# - 1e-4 for 33b & 64b
learning_rate: 0.0002
train_on_inputs: false
group_by_length: false
bf16: true
fp16: false
tf32: true
gradient_checkpointing: true
# stop training after this many evaluation losses have increased in a row
# https://huggingface.co/transformers/v4.2.2/_modules/transformers/trainer_callback.html#EarlyStoppingCallback
# early_stopping_patience: 3
resume_from_checkpoint:
auto_resume_from_checkpoints: true
local_rank:
logging_steps: 1
xformers_attention: true
flash_attention:
gptq_groupsize:
gptq_model_v1:
warmup_steps: 10
eval_steps: 5
save_steps: 10
debug:
deepspeed:
weight_decay: 0.01
adam_beta1:
adam_beta2: 0.999
adam_epsilon:
# Gradient clipping max norm
max_grad_norm: 0.3
fsdp:
fsdp_config:
special_tokens:
pad_token: "<|endoftext|>"
bos_token: ">>ABSTRACT<<"
eos_token: "<|endoftext|>"
Writing examples/falcon/config-40b-qlora.yml
%env ACCELERATE_USE_DEEPSPEED=true
%%writefile scripts/ft.py
import os
from pathlib import Path
import fire
import logging
import finetune
from axolotl.utils.trainer import setup_trainer as setup_trainer_orig
logging.basicConfig(level=os.getenv("LOG_LEVEL", "INFO"))
def train_ex(
config: Path = Path("configs/"),
prepare_ds_only: bool = False,
**kwargs,
):
logging.info('train_ex before')
finetune.train(config, prepare_ds_only, **kwargs)
logging.info('train_ex after')
def setup_trainer_ex(cfg, train_dataset, eval_dataset, model, tokenizer):
logging.info('setup_trainer_ex before')
logging.info(f'cfg.some_config = {cfg.some_config}')
trainer = setup_trainer_orig(cfg, train_dataset, eval_dataset, model, tokenizer)
logging.info('setup_trainer_ex after')
return trainer
finetune.setup_trainer = setup_trainer_ex
if __name__ == "__main__":
fire.Fire(train_ex)
Writing scripts/ft.py
%env HF_HUB_DISABLE_PROGRESS_BARS=1
env: HF_HUB_DISABLE_PROGRESS_BARS=1
%env ACCELERATE_USE_DEEPSPEED=false
env: ACCELERATE_USE_DEEPSPEED=false
%cd /workspace/axolotl
/workspace/axolotl
!cat examples/falcon/config-40b-qlora.yml
# 1b: tiiuae/falcon-rw-1b # 7b: tiiuae/falcon-7b # 40b: tiiuae/falcon-40b base_model: /content/llm-playground/models/tiiuae_falcon-40b base_model_config: /content/llm-playground/models/tiiuae_falcon-40b # required by falcon custom model code: https://huggingface.co/tiiuae/falcon-7b/tree/main trust_remote_code: true model_type: AutoModelForCausalLM tokenizer_type: AutoTokenizer load_in_8bit: false # enable 4bit for QLoRA load_in_4bit: true gptq: false strict: false push_dataset_to_hub: utensil hf_use_auth_token: true datasets: - path: winglian/evals data_files: - hf/ARC-Challenge.jsonl - hf/ARC-Easy.jsonl - hf/riddle_sense.jsonl type: explainchoice:chat - path: winglian/evals data_files: - hf/gsm8k.jsonl - hf/winogrande.jsonl type: alpaca_chat.load_qa - path: winglian/evals data_files: - custom/n_task.jsonl - custom/misconceptions.jsonl - custom/context_insensitivity.jsonl type: alpaca_chat - path: camel-ai/math type: alpaca_chat.load_camel_ai - path: camel-ai/biology type: alpaca_chat.load_camel_ai - path: camel-ai/physics type: alpaca_chat.load_camel_ai - path: camel-ai/chemistry type: alpaca_chat.load_camel_ai - path: winglian/evals data_files: - custom/in_context_qa.jsonl type: context_qa - path: winglian/evals data_files: - custom/in_context_qa.jsonl type: context_qa.load_404 - path: winglian/evals data_files: - custom/jokes_explained_500up.jsonl type: sharegpt_jokes - path: winglian/evals data_files: - custom/classify-self-chat.sharegpt.jsonl - custom/coding-self-chat.sharegpt.jsonl - custom/prose-gpt4.sharegpt.jsonl - custom/prose-rewrite-gpt4.sharegpt.jsonl type: sharegpt_simple.load_role - path: winglian/evals data_files: - openai/tldr.jsonl type: summarizetldr:chat - path: winglian/evals data_files: - hellaswag/hellaswag.jsonl type: explainchoice:chat - path: metaeval/ScienceQA_text_only type: concisechoice:chat - path: teknium/GPT4-LLM-Cleaned type: alpaca_chat - path: teknium/GPTeacher-General-Instruct data_files: gpt4-instruct-similarity-0.6-dataset.json type: gpteacher:chat - path: QingyiSi/Alpaca-CoT data_files: - Chain-of-Thought/formatted_cot_data/aqua_train.json - Chain-of-Thought/formatted_cot_data/creak_train.json - Chain-of-Thought/formatted_cot_data/ecqa_train.json - Chain-of-Thought/formatted_cot_data/esnli_train.json - Chain-of-Thought/formatted_cot_data/qasc_train.json - Chain-of-Thought/formatted_cot_data/qed_train.json - Chain-of-Thought/formatted_cot_data/sensemaking_train.json - Chain-of-Thought/formatted_cot_data/strategyqa_train.json - GPTeacher/Roleplay/formatted_roleplay-similarity_0.6-instruct-dataset.json type: alpaca_chat - path: ehartford/WizardLM_alpaca_evol_instruct_70k_unfiltered type: alpaca_chat - path: ehartford/wizard_vicuna_70k_unfiltered type: sharegpt:chat dataset_prepared_path: last_run_prepared val_set_size: 0.01 # enable QLoRA adapter: qlora lora_model_dir: sequence_len: 2048 max_packed_sequence_len: 2048 # hyperparameters from QLoRA paper Appendix B.2 # "We find hyperparameters to be largely robust across datasets" lora_r: 64 lora_alpha: 16 # 0.1 for models up to 13B # 0.05 for 33B and 65B models lora_dropout: 0.05 # add LoRA modules on all linear layers of the base model lora_target_modules: lora_target_linear: true lora_fan_in_fan_out: wandb_project: falcon-qlora wandb_watch: wandb_run_id: wandb_log_model: output_dir: /content/axolotl-trained/falcon-qlora-40b-minotaur/ # QLoRA paper Table 9 # - 16 for 7b & 13b # - 32 for 33b, 64 for 64b # Max size tested on A6000 # - 7b: 40 # - 40b: 4 # decrease if OOM, increase for max VRAM utilization micro_batch_size: 4 gradient_accumulation_steps: 1 num_epochs: 3 # Optimizer for QLoRA optimizer: paged_adamw_32bit torchdistx_path: lr_scheduler: cosine # QLoRA paper Table 9 # - 2e-4 for 7b & 13b # - 1e-4 for 33b & 64b learning_rate: 0.0002 train_on_inputs: false group_by_length: false bf16: true fp16: false tf32: true gradient_checkpointing: true # stop training after this many evaluation losses have increased in a row # https://huggingface.co/transformers/v4.2.2/_modules/transformers/trainer_callback.html#EarlyStoppingCallback # early_stopping_patience: 3 resume_from_checkpoint: auto_resume_from_checkpoints: true local_rank: logging_steps: 1 xformers_attention: true flash_attention: gptq_groupsize: gptq_model_v1: warmup_steps: 10 eval_steps: 5 save_steps: 10 debug: deepspeed: weight_decay: 0.01 adam_beta1: adam_beta2: 0.999 adam_epsilon: # Gradient clipping max norm max_grad_norm: 0.3 fsdp: fsdp_config: special_tokens: pad_token: "<|endoftext|>" bos_token: ">>ABSTRACT<<" eos_token: "<|endoftext|>"
#%%writefile examples/falcon/config-40b-qlora.yml
!accelerate launch scripts/finetune.py examples/falcon/config-40b-qlora.yml
Setting ds_accelerator to cuda (auto detect) The following values were not passed to `accelerate launch` and had defaults used instead: `--num_processes` was set to a value of `2` More than one GPU was found, enabling multi-GPU training. If this was unintended please pass in `--num_processes=1`. `--num_machines` was set to a value of `1` `--mixed_precision` was set to a value of `'no'` `--dynamo_backend` was set to a value of `'no'` To avoid this warning pass in values for each of the problematic parameters or run `accelerate config`. Setting ds_accelerator to cuda (auto detect) Setting ds_accelerator to cuda (auto detect) ===================================BUG REPORT=================================== Welcome to bitsandbytes. For bug reports, please run python -m bitsandbytes and submit this information together with your error trace to: https://github.com/TimDettmers/bitsandbytes/issues ================================================================================ ===================================BUG REPORT=================================== Welcome to bitsandbytes. For bug reports, please run python -m bitsandbytes and submit this information together with your error trace to: https://github.com/TimDettmers/bitsandbytes/issues ================================================================================ bin /root/miniconda3/envs/py3.9/lib/python3.9/site-packages/bitsandbytes-0.39.0-py3.9.egg/bitsandbytes/libbitsandbytes_cuda118.so /root/miniconda3/envs/py3.9/lib/python3.9/site-packages/bitsandbytes-0.39.0-py3.9.egg/bitsandbytes/cuda_setup/main.py:149: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('/usr/local/nvidia/lib'), PosixPath('/usr/local/nvidia/lib64')} warn(msg) /root/miniconda3/envs/py3.9/lib/python3.9/site-packages/bitsandbytes-0.39.0-py3.9.egg/bitsandbytes/cuda_setup/main.py:149: UserWarning: /usr/local/nvidia/lib:/usr/local/nvidia/lib64 did not contain ['libcudart.so', 'libcudart.so.11.0', 'libcudart.so.12.0'] as expected! Searching further paths... warn(msg) /root/miniconda3/envs/py3.9/lib/python3.9/site-packages/bitsandbytes-0.39.0-py3.9.egg/bitsandbytes/cuda_setup/main.py:149: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('//matplotlib_inline.backend_inline'), PosixPath('module')} warn(msg) /root/miniconda3/envs/py3.9/lib/python3.9/site-packages/bitsandbytes-0.39.0-py3.9.egg/bitsandbytes/cuda_setup/main.py:149: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('ssh-rsa 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 utensil@Utensils-MacBook-Pro.local')} warn(msg) /root/miniconda3/envs/py3.9/lib/python3.9/site-packages/bitsandbytes-0.39.0-py3.9.egg/bitsandbytes/cuda_setup/main.py:149: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('/tmp/torchelastic_dvz1krnf/none_vrp7sfn2/attempt_0/1/error.json')} warn(msg) CUDA_SETUP: WARNING! libcudart.so not found in any environmental path. Searching in backup paths... /root/miniconda3/envs/py3.9/lib/python3.9/site-packages/bitsandbytes-0.39.0-py3.9.egg/bitsandbytes/cuda_setup/main.py:149: UserWarning: Found duplicate ['libcudart.so', 'libcudart.so.11.0', 'libcudart.so.12.0'] files: {PosixPath('/usr/local/cuda/lib64/libcudart.so'), PosixPath('/usr/local/cuda/lib64/libcudart.so.11.0')}.. We'll flip a coin and try one of these, in order to fail forward. Either way, this might cause trouble in the future: If you get `CUDA error: invalid device function` errors, the above might be the cause and the solution is to make sure only one ['libcudart.so', 'libcudart.so.11.0', 'libcudart.so.12.0'] in the paths that we search based on your env. warn(msg) CUDA SETUP: CUDA runtime path found: /usr/local/cuda/lib64/libcudart.so CUDA SETUP: Highest compute capability among GPUs detected: 8.0 CUDA SETUP: Detected CUDA version 118 CUDA SETUP: Loading binary /root/miniconda3/envs/py3.9/lib/python3.9/site-packages/bitsandbytes-0.39.0-py3.9.egg/bitsandbytes/libbitsandbytes_cuda118.so... bin /root/miniconda3/envs/py3.9/lib/python3.9/site-packages/bitsandbytes-0.39.0-py3.9.egg/bitsandbytes/libbitsandbytes_cuda118.so /root/miniconda3/envs/py3.9/lib/python3.9/site-packages/bitsandbytes-0.39.0-py3.9.egg/bitsandbytes/cuda_setup/main.py:149: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('/usr/local/nvidia/lib'), PosixPath('/usr/local/nvidia/lib64')} warn(msg) /root/miniconda3/envs/py3.9/lib/python3.9/site-packages/bitsandbytes-0.39.0-py3.9.egg/bitsandbytes/cuda_setup/main.py:149: UserWarning: /usr/local/nvidia/lib:/usr/local/nvidia/lib64 did not contain ['libcudart.so', 'libcudart.so.11.0', 'libcudart.so.12.0'] as expected! Searching further paths... warn(msg) /root/miniconda3/envs/py3.9/lib/python3.9/site-packages/bitsandbytes-0.39.0-py3.9.egg/bitsandbytes/cuda_setup/main.py:149: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('module'), PosixPath('//matplotlib_inline.backend_inline')} warn(msg) /root/miniconda3/envs/py3.9/lib/python3.9/site-packages/bitsandbytes-0.39.0-py3.9.egg/bitsandbytes/cuda_setup/main.py:149: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('ssh-rsa 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 utensil@Utensils-MacBook-Pro.local')} warn(msg) /root/miniconda3/envs/py3.9/lib/python3.9/site-packages/bitsandbytes-0.39.0-py3.9.egg/bitsandbytes/cuda_setup/main.py:149: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('/tmp/torchelastic_dvz1krnf/none_vrp7sfn2/attempt_0/0/error.json')} warn(msg) CUDA_SETUP: WARNING! libcudart.so not found in any environmental path. Searching in backup paths... /root/miniconda3/envs/py3.9/lib/python3.9/site-packages/bitsandbytes-0.39.0-py3.9.egg/bitsandbytes/cuda_setup/main.py:149: UserWarning: Found duplicate ['libcudart.so', 'libcudart.so.11.0', 'libcudart.so.12.0'] files: {PosixPath('/usr/local/cuda/lib64/libcudart.so.11.0'), PosixPath('/usr/local/cuda/lib64/libcudart.so')}.. We'll flip a coin and try one of these, in order to fail forward. Either way, this might cause trouble in the future: If you get `CUDA error: invalid device function` errors, the above might be the cause and the solution is to make sure only one ['libcudart.so', 'libcudart.so.11.0', 'libcudart.so.12.0'] in the paths that we search based on your env. warn(msg) CUDA SETUP: CUDA runtime path found: /usr/local/cuda/lib64/libcudart.so.11.0 CUDA SETUP: Highest compute capability among GPUs detected: 8.0 CUDA SETUP: Detected CUDA version 118 CUDA SETUP: Loading binary /root/miniconda3/envs/py3.9/lib/python3.9/site-packages/bitsandbytes-0.39.0-py3.9.egg/bitsandbytes/libbitsandbytes_cuda118.so... WARNING:root:`trust_remote_code` is set to true. Please make sure that you reviewed the remote code/model. INFO:root:loading tokenizer... /content/llm-playground/models/tiiuae_falcon-40b WARNING:root:`trust_remote_code` is set to true. Please make sure that you reviewed the remote code/model. INFO:root:loading tokenizer... /content/llm-playground/models/tiiuae_falcon-40b Using bos_token, but it is not set yet. Using pad_token, but it is not set yet. Using unk_token, but it is not set yet. INFO:root:Checking for packed prepared dataset from hub... utensil/216aa4e2be3974d0a1d25d8c19db01a4 Using bos_token, but it is not set yet. Using pad_token, but it is not set yet. Using unk_token, but it is not set yet. INFO:root:Checking for packed prepared dataset from hub... utensil/216aa4e2be3974d0a1d25d8c19db01a4 WARNING:datasets.builder:Found cached dataset parquet (/root/.cache/huggingface/datasets/utensil___parquet/utensil--9a63aa2c07ace8350a0e8b32ab913f2a-9cb79670bc460bd7/0.0.0/14a00e99c0d15a23649d0db8944380ac81082d4b021f398733dd84f3a6c569a7) 100%|████████████████████████████████████████████| 1/1 [00:00<00:00, 127.56it/s] INFO:root:packing master dataset to len: 2048 WARNING:datasets.builder:Found cached dataset parquet (/root/.cache/huggingface/datasets/utensil___parquet/utensil--9a63aa2c07ace8350a0e8b32ab913f2a-9cb79670bc460bd7/0.0.0/14a00e99c0d15a23649d0db8944380ac81082d4b021f398733dd84f3a6c569a7) 100%|████████████████████████████████████████████| 1/1 [00:00<00:00, 129.49it/s] INFO:root:packing master dataset to len: 2048 INFO:root:loading model and peft_config... 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INFO:root:converting PEFT model w/ prepare_model_for_kbit_training INFO:root:found linear modules: ['dense_4h_to_h', 'dense_h_to_4h', 'query_key_value', 'dense'] Pushing dataset shards to the dataset hub: 80%|█▌| 4/5 [01:30<00:23, 23.12s/it] Creating parquet from Arrow format: 0%| | 0/20 [00:00<?, ?ba/s] Creating parquet from Arrow format: 5%|▍ | 1/20 [00:00<00:02, 9.50ba/s] Creating parquet from Arrow format: 15%|█▏ | 3/20 [00:00<00:01, 9.88ba/s] Creating parquet from Arrow format: 25%|██ | 5/20 [00:00<00:01, 9.98ba/s] Creating parquet from Arrow format: 35%|██▊ | 7/20 [00:00<00:01, 10.03ba/s] Creating parquet from Arrow format: 45%|███▌ | 9/20 [00:00<00:01, 10.13ba/s] Creating parquet from Arrow format: 55%|███▊ | 11/20 [00:01<00:00, 10.20ba/s] Creating parquet from Arrow format: 65%|████▌ | 13/20 [00:01<00:00, 9.80ba/s] Creating parquet from Arrow format: 75%|█████▎ | 15/20 [00:01<00:00, 9.93ba/s] Creating parquet from Arrow format: 85%|█████▉ | 17/20 [00:01<00:00, 10.13ba/s] 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Loading checkpoint shards: 100%|██████████████████| 9/9 [01:19<00:00, 8.86s/it] INFO:root:converting PEFT model w/ prepare_model_for_kbit_training INFO:root:found linear modules: ['dense_h_to_4h', 'dense_4h_to_h', 'dense', 'query_key_value'] trainable params: 444,334,080 || all params: 21,363,310,592 || trainable%: 2.0798933671188187 INFO:torch.distributed.distributed_c10d:Added key: store_based_barrier_key:1 to store for rank: 1 INFO:torch.distributed.distributed_c10d:Waiting in store based barrier to initialize process group for rank: 1, key: store_based_barrier_key:1 (world_size=2, worker_count=1, timeout=0:30:00) INFO:torch.distributed.distributed_c10d:Waiting in store based barrier to initialize process group for rank: 1, key: store_based_barrier_key:1 (world_size=2, worker_count=1, timeout=0:30:00) INFO:torch.distributed.distributed_c10d:Waiting in store based barrier to initialize process group for rank: 1, key: store_based_barrier_key:1 (world_size=2, worker_count=1, timeout=0:30:00) INFO:torch.distributed.distributed_c10d:Waiting in store based barrier to initialize process group for rank: 1, key: store_based_barrier_key:1 (world_size=2, worker_count=1, timeout=0:30:00) INFO:torch.distributed.distributed_c10d:Waiting in store based barrier to initialize process group for rank: 1, key: store_based_barrier_key:1 (world_size=2, worker_count=1, timeout=0:30:00) INFO:torch.distributed.distributed_c10d:Waiting in store based barrier to initialize process group for rank: 1, key: store_based_barrier_key:1 (world_size=2, worker_count=1, timeout=0:30:00) INFO:torch.distributed.distributed_c10d:Waiting in store based barrier to initialize process group for rank: 1, key: store_based_barrier_key:1 (world_size=2, worker_count=1, timeout=0:30:00) INFO:torch.distributed.distributed_c10d:Waiting in store based barrier to initialize process group for rank: 1, key: store_based_barrier_key:1 (world_size=2, worker_count=1, timeout=0:30:00) INFO:torch.distributed.distributed_c10d:Waiting in store based barrier to initialize process group for rank: 1, key: store_based_barrier_key:1 (world_size=2, worker_count=1, timeout=0:30:00) INFO:torch.distributed.distributed_c10d:Waiting in store based barrier to initialize process group for rank: 1, key: store_based_barrier_key:1 (world_size=2, worker_count=1, timeout=0:30:00) INFO:torch.distributed.distributed_c10d:Waiting in store based barrier to initialize process group for rank: 1, key: store_based_barrier_key:1 (world_size=2, worker_count=1, timeout=0:30:00) INFO:torch.distributed.distributed_c10d:Waiting in store based barrier to initialize process group for rank: 1, key: store_based_barrier_key:1 (world_size=2, worker_count=1, timeout=0:30:00) trainable params: 444,334,080 || all params: 21,363,310,592 || trainable%: 2.0798933671188187 INFO:torch.distributed.distributed_c10d:Added key: store_based_barrier_key:1 to store for rank: 0 INFO:torch.distributed.distributed_c10d:Rank 0: Completed store-based barrier for key:store_based_barrier_key:1 with 2 nodes. INFO:torch.distributed.distributed_c10d:Rank 1: Completed store-based barrier for key:store_based_barrier_key:1 with 2 nodes. INFO:root:Compiling torch model INFO:root:Compiling torch model INFO:root:Pre-saving adapter config to /content/axolotl-trained/falcon-qlora-40b-minotaur/ INFO:root:Starting trainer... INFO:root:Pre-saving adapter config to /content/axolotl-trained/falcon-qlora-40b-minotaur/ INFO:root:Starting trainer... wandb: Currently logged in as: utensil. Use `wandb login --relogin` to force relogin wandb: Tracking run with wandb version 0.15.4 wandb: Run data is saved locally in /workspace/axolotl/wandb/run-20230616_065554-6gav9vad wandb: Run `wandb offline` to turn off syncing. wandb: Syncing run solar-violet-45 wandb: ⭐️ View project at https://wandb.ai/utensil/falcon-qlora wandb: 🚀 View run at https://wandb.ai/utensil/falcon-qlora/runs/6gav9vad 0%| | 0/35325 [00:00<?, ?it/s]You're using a PreTrainedTokenizerFast tokenizer. Please note that with a fast tokenizer, using the `__call__` method is faster than using a method to encode the text followed by a call to the `pad` method to get a padded encoding. You're using a PreTrainedTokenizerFast tokenizer. Please note that with a fast tokenizer, using the `__call__` method is faster than using a method to encode the text followed by a call to the `pad` method to get a padded encoding. {'loss': 1.4081, 'learning_rate': 2e-05, 'epoch': 0.0} 0%| | 1/35325 [00:16<161:17:41, 16.44s/it]INFO:torch.nn.parallel.distributed:Reducer buckets have been rebuilt in this iteration. 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| 25/119 [01:58<07:51, 5.01s/it] 22%|█████████▏ | 26/119 [02:03<07:42, 4.97s/it] 23%|█████████▌ | 27/119 [02:08<07:35, 4.95s/it] 24%|█████████▉ | 28/119 [02:13<07:38, 5.04s/it] 24%|██████████▏ | 29/119 [02:18<07:33, 5.04s/it] 25%|██████████▌ | 30/119 [02:23<07:27, 5.02s/it] 26%|██████████▉ | 31/119 [02:28<07:15, 4.95s/it] 27%|███████████▎ | 32/119 [02:33<07:11, 4.96s/it]^C WARNING:torch.distributed.elastic.agent.server.api:Received 2 death signal, shutting down workers WARNING:torch.distributed.elastic.multiprocessing.api:Sending process 2528 closing signal SIGINT WARNING:torch.distributed.elastic.multiprocessing.api:Sending process 2529 closing signal SIGINT Traceback (most recent call last): File "/workspace/axolotl/scripts/finetune.py", line 352, in <module> fire.Fire(train) File "/root/miniconda3/envs/py3.9/lib/python3.9/site-packages/fire/core.py", line 141, in Fire component_trace = _Fire(component, args, parsed_flag_args, context, name) File "/root/miniconda3/envs/py3.9/lib/python3.9/site-packages/fire/core.py", line 475, in _Fire component, remaining_args = _CallAndUpdateTrace( File "/root/miniconda3/envs/py3.9/lib/python3.9/site-packages/fire/core.py", line 691, in _CallAndUpdateTrace component = fn(*varargs, **kwargs) File "/workspace/axolotl/scripts/finetune.py", line 337, in train trainer.train(resume_from_checkpoint=resume_from_checkpoint) File "/root/miniconda3/envs/py3.9/lib/python3.9/site-packages/transformers/trainer.py", line 1540, in train return inner_training_loop( File "/root/miniconda3/envs/py3.9/lib/python3.9/site-packages/transformers/trainer.py", line 1884, in _inner_training_loop self._maybe_log_save_evaluate(tr_loss, model, trial, epoch, ignore_keys_for_eval) File "/root/miniconda3/envs/py3.9/lib/python3.9/site-packages/transformers/trainer.py", line 2185, in _maybe_log_save_evaluate metrics = self.evaluate(ignore_keys=ignore_keys_for_eval) File "/root/miniconda3/envs/py3.9/lib/python3.9/site-packages/transformers/trainer.py", line 2931, in evaluate output = eval_loop( File "/root/miniconda3/envs/py3.9/lib/python3.9/site-packages/transformers/trainer.py", line 3120, in evaluation_loop loss, logits, labels = self.prediction_step(model, inputs, prediction_loss_only, ignore_keys=ignore_keys) File "/root/miniconda3/envs/py3.9/lib/python3.9/site-packages/transformers/trainer.py", line 3363, in prediction_step loss, outputs = self.compute_loss(model, inputs, return_outputs=True) File "/root/miniconda3/envs/py3.9/lib/python3.9/site-packages/transformers/trainer.py", line 2662, in compute_loss outputs = model(**inputs) File "/root/miniconda3/envs/py3.9/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl return forward_call(*args, **kwargs) File "/root/miniconda3/envs/py3.9/lib/python3.9/site-packages/peft/peft_model.py", line 785, in forward return self.base_model( File "/root/miniconda3/envs/py3.9/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl return forward_call(*args, **kwargs) File "/root/miniconda3/envs/py3.9/lib/python3.9/site-packages/accelerate/hooks.py", line 165, in new_forward output = old_forward(*args, **kwargs) File "/root/.cache/huggingface/modules/transformers_modules/tiiuae_falcon-40b/modelling_RW.py", line 759, in forward transformer_outputs = self.transformer( File "/root/miniconda3/envs/py3.9/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl return forward_call(*args, **kwargs) File "/root/miniconda3/envs/py3.9/lib/python3.9/site-packages/accelerate/hooks.py", line 165, in new_forward output = old_forward(*args, **kwargs) File "/root/.cache/huggingface/modules/transformers_modules/tiiuae_falcon-40b/modelling_RW.py", line 654, in forward outputs = block( File "/root/miniconda3/envs/py3.9/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl return forward_call(*args, **kwargs) File "/root/miniconda3/envs/py3.9/lib/python3.9/site-packages/accelerate/hooks.py", line 165, in new_forward output = old_forward(*args, **kwargs) File "/root/.cache/huggingface/modules/transformers_modules/tiiuae_falcon-40b/modelling_RW.py", line 396, in forward attn_outputs = self.self_attention( File "/root/miniconda3/envs/py3.9/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl return forward_call(*args, **kwargs) File "/root/miniconda3/envs/py3.9/lib/python3.9/site-packages/accelerate/hooks.py", line 165, in new_forward output = old_forward(*args, **kwargs) File "/root/.cache/huggingface/modules/transformers_modules/tiiuae_falcon-40b/modelling_RW.py", line 255, in forward (query_layer, key_layer, value_layer) = self._split_heads(fused_qkv) File "/root/.cache/huggingface/modules/transformers_modules/tiiuae_falcon-40b/modelling_RW.py", line 201, in _split_heads k = qkv[:, :, :, [-2]] KeyboardInterrupt
%env ACCELERATE_USE_DEEPSPEED=false
env: ACCELERATE_USE_DEEPSPEED=false
!cat examples/falcon/config-40b-qlora.yml
# 1b: tiiuae/falcon-rw-1b # 7b: tiiuae/falcon-7b # 40b: tiiuae/falcon-40b base_model: /content/llm-playground/models/tiiuae_falcon-40b base_model_config: /content/llm-playground/models/tiiuae_falcon-40b # required by falcon custom model code: https://huggingface.co/tiiuae/falcon-7b/tree/main trust_remote_code: true model_type: AutoModelForCausalLM tokenizer_type: AutoTokenizer load_in_8bit: false # enable 4bit for QLoRA load_in_4bit: true gptq: false strict: false push_dataset_to_hub: utensil hf_use_auth_token: true datasets: - path: winglian/evals data_files: - hf/ARC-Challenge.jsonl - hf/ARC-Easy.jsonl - hf/riddle_sense.jsonl type: explainchoice:chat - path: winglian/evals data_files: - hf/gsm8k.jsonl - hf/winogrande.jsonl type: alpaca_chat.load_qa - path: winglian/evals data_files: - custom/n_task.jsonl - custom/misconceptions.jsonl - custom/context_insensitivity.jsonl type: alpaca_chat - path: camel-ai/math type: alpaca_chat.load_camel_ai - path: camel-ai/biology type: alpaca_chat.load_camel_ai - path: camel-ai/physics type: alpaca_chat.load_camel_ai - path: camel-ai/chemistry type: alpaca_chat.load_camel_ai - path: winglian/evals data_files: - custom/in_context_qa.jsonl type: context_qa - path: winglian/evals data_files: - custom/in_context_qa.jsonl type: context_qa.load_404 - path: winglian/evals data_files: - custom/jokes_explained_500up.jsonl type: sharegpt_jokes - path: winglian/evals data_files: - custom/classify-self-chat.sharegpt.jsonl - custom/coding-self-chat.sharegpt.jsonl - custom/prose-gpt4.sharegpt.jsonl - custom/prose-rewrite-gpt4.sharegpt.jsonl type: sharegpt_simple.load_role - path: winglian/evals data_files: - openai/tldr.jsonl type: summarizetldr:chat - path: winglian/evals data_files: - hellaswag/hellaswag.jsonl type: explainchoice:chat - path: metaeval/ScienceQA_text_only type: concisechoice:chat - path: teknium/GPT4-LLM-Cleaned type: alpaca_chat - path: teknium/GPTeacher-General-Instruct data_files: gpt4-instruct-similarity-0.6-dataset.json type: gpteacher:chat - path: QingyiSi/Alpaca-CoT data_files: - Chain-of-Thought/formatted_cot_data/aqua_train.json - Chain-of-Thought/formatted_cot_data/creak_train.json - Chain-of-Thought/formatted_cot_data/ecqa_train.json - Chain-of-Thought/formatted_cot_data/esnli_train.json - Chain-of-Thought/formatted_cot_data/qasc_train.json - Chain-of-Thought/formatted_cot_data/qed_train.json - Chain-of-Thought/formatted_cot_data/sensemaking_train.json - Chain-of-Thought/formatted_cot_data/strategyqa_train.json - GPTeacher/Roleplay/formatted_roleplay-similarity_0.6-instruct-dataset.json type: alpaca_chat - path: ehartford/WizardLM_alpaca_evol_instruct_70k_unfiltered type: alpaca_chat - path: ehartford/wizard_vicuna_70k_unfiltered type: sharegpt:chat dataset_prepared_path: last_run_prepared val_set_size: 0.01 # enable QLoRA adapter: qlora lora_model_dir: sequence_len: 2048 max_packed_sequence_len: 2048 # hyperparameters from QLoRA paper Appendix B.2 # "We find hyperparameters to be largely robust across datasets" lora_r: 64 lora_alpha: 16 # 0.1 for models up to 13B # 0.05 for 33B and 65B models lora_dropout: 0.05 # add LoRA modules on all linear layers of the base model lora_target_modules: lora_target_linear: true lora_fan_in_fan_out: wandb_project: falcon-qlora wandb_watch: wandb_run_id: wandb_log_model: output_dir: /content/axolotl-trained/falcon-qlora-40b-minotaur/ # QLoRA paper Table 9 # - 16 for 7b & 13b # - 32 for 33b, 64 for 64b # Max size tested on A6000 # - 7b: 40 # - 40b: 4 # decrease if OOM, increase for max VRAM utilization micro_batch_size: 4 gradient_accumulation_steps: 1 num_epochs: 3 # Optimizer for QLoRA optimizer: adamw_bnb_8bit torchdistx_path: lr_scheduler: cosine # QLoRA paper Table 9 # - 2e-4 for 7b & 13b # - 1e-4 for 33b & 64b learning_rate: 0.0002 train_on_inputs: false group_by_length: false bf16: true fp16: false tf32: true gradient_checkpointing: true # stop training after this many evaluation losses have increased in a row # https://huggingface.co/transformers/v4.2.2/_modules/transformers/trainer_callback.html#EarlyStoppingCallback # early_stopping_patience: 3 resume_from_checkpoint: auto_resume_from_checkpoints: true local_rank: logging_steps: 1 xformers_attention: true flash_attention: gptq_groupsize: gptq_model_v1: warmup_steps: 10 eval_steps: 5 save_steps: 10 debug: deepspeed: weight_decay: 0.01 adam_beta1: adam_beta2: 0.999 adam_epsilon: # Gradient clipping max norm max_grad_norm: 0.3 fsdp: fsdp_config: special_tokens: pad_token: "<|endoftext|>" bos_token: ">>ABSTRACT<<" eos_token: "<|endoftext|>"
!ds_report
#%%writefile examples/falcon/config-40b-qlora.yml
!accelerate launch scripts/finetune.py examples/falcon/config-40b-qlora.yml
Setting ds_accelerator to cuda (auto detect) The following values were not passed to `accelerate launch` and had defaults used instead: `--num_processes` was set to a value of `2` More than one GPU was found, enabling multi-GPU training. If this was unintended please pass in `--num_processes=1`. `--num_machines` was set to a value of `1` `--mixed_precision` was set to a value of `'no'` `--dynamo_backend` was set to a value of `'no'` To avoid this warning pass in values for each of the problematic parameters or run `accelerate config`. Setting ds_accelerator to cuda (auto detect) Setting ds_accelerator to cuda (auto detect) ===================================BUG REPORT=================================== Welcome to bitsandbytes. For bug reports, please run python -m bitsandbytes and submit this information together with your error trace to: https://github.com/TimDettmers/bitsandbytes/issues ================================================================================ ===================================BUG REPORT=================================== Welcome to bitsandbytes. For bug reports, please run python -m bitsandbytes and submit this information together with your error trace to: https://github.com/TimDettmers/bitsandbytes/issues ================================================================================ bin /root/miniconda3/envs/py3.9/lib/python3.9/site-packages/bitsandbytes-0.39.0-py3.9.egg/bitsandbytes/libbitsandbytes_cuda118.so /root/miniconda3/envs/py3.9/lib/python3.9/site-packages/bitsandbytes-0.39.0-py3.9.egg/bitsandbytes/cuda_setup/main.py:149: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('/usr/local/nvidia/lib64'), PosixPath('/usr/local/nvidia/lib')} warn(msg) /root/miniconda3/envs/py3.9/lib/python3.9/site-packages/bitsandbytes-0.39.0-py3.9.egg/bitsandbytes/cuda_setup/main.py:149: UserWarning: /usr/local/nvidia/lib:/usr/local/nvidia/lib64 did not contain ['libcudart.so', 'libcudart.so.11.0', 'libcudart.so.12.0'] as expected! Searching further paths... warn(msg) /root/miniconda3/envs/py3.9/lib/python3.9/site-packages/bitsandbytes-0.39.0-py3.9.egg/bitsandbytes/cuda_setup/main.py:149: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('//matplotlib_inline.backend_inline'), PosixPath('module')} warn(msg) /root/miniconda3/envs/py3.9/lib/python3.9/site-packages/bitsandbytes-0.39.0-py3.9.egg/bitsandbytes/cuda_setup/main.py:149: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('ssh-rsa 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 utensil@Utensils-MacBook-Pro.local')} warn(msg) /root/miniconda3/envs/py3.9/lib/python3.9/site-packages/bitsandbytes-0.39.0-py3.9.egg/bitsandbytes/cuda_setup/main.py:149: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('/tmp/torchelastic_av2jw5za/none_skuvdgy8/attempt_0/0/error.json')} warn(msg) CUDA_SETUP: WARNING! libcudart.so not found in any environmental path. Searching in backup paths... /root/miniconda3/envs/py3.9/lib/python3.9/site-packages/bitsandbytes-0.39.0-py3.9.egg/bitsandbytes/cuda_setup/main.py:149: UserWarning: Found duplicate ['libcudart.so', 'libcudart.so.11.0', 'libcudart.so.12.0'] files: {PosixPath('/usr/local/cuda/lib64/libcudart.so.11.0'), PosixPath('/usr/local/cuda/lib64/libcudart.so')}.. We'll flip a coin and try one of these, in order to fail forward. Either way, this might cause trouble in the future: If you get `CUDA error: invalid device function` errors, the above might be the cause and the solution is to make sure only one ['libcudart.so', 'libcudart.so.11.0', 'libcudart.so.12.0'] in the paths that we search based on your env. warn(msg) CUDA SETUP: CUDA runtime path found: /usr/local/cuda/lib64/libcudart.so.11.0 CUDA SETUP: Highest compute capability among GPUs detected: 8.0 CUDA SETUP: Detected CUDA version 118 CUDA SETUP: Loading binary /root/miniconda3/envs/py3.9/lib/python3.9/site-packages/bitsandbytes-0.39.0-py3.9.egg/bitsandbytes/libbitsandbytes_cuda118.so... bin /root/miniconda3/envs/py3.9/lib/python3.9/site-packages/bitsandbytes-0.39.0-py3.9.egg/bitsandbytes/libbitsandbytes_cuda118.so /root/miniconda3/envs/py3.9/lib/python3.9/site-packages/bitsandbytes-0.39.0-py3.9.egg/bitsandbytes/cuda_setup/main.py:149: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('/usr/local/nvidia/lib'), PosixPath('/usr/local/nvidia/lib64')} warn(msg) /root/miniconda3/envs/py3.9/lib/python3.9/site-packages/bitsandbytes-0.39.0-py3.9.egg/bitsandbytes/cuda_setup/main.py:149: UserWarning: /usr/local/nvidia/lib:/usr/local/nvidia/lib64 did not contain ['libcudart.so', 'libcudart.so.11.0', 'libcudart.so.12.0'] as expected! Searching further paths... warn(msg) /root/miniconda3/envs/py3.9/lib/python3.9/site-packages/bitsandbytes-0.39.0-py3.9.egg/bitsandbytes/cuda_setup/main.py:149: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('//matplotlib_inline.backend_inline'), PosixPath('module')} warn(msg) /root/miniconda3/envs/py3.9/lib/python3.9/site-packages/bitsandbytes-0.39.0-py3.9.egg/bitsandbytes/cuda_setup/main.py:149: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('ssh-rsa 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 utensil@Utensils-MacBook-Pro.local')} warn(msg) /root/miniconda3/envs/py3.9/lib/python3.9/site-packages/bitsandbytes-0.39.0-py3.9.egg/bitsandbytes/cuda_setup/main.py:149: UserWarning: WARNING: The following directories listed in your path were found to be non-existent: {PosixPath('/tmp/torchelastic_av2jw5za/none_skuvdgy8/attempt_0/1/error.json')} warn(msg) CUDA_SETUP: WARNING! libcudart.so not found in any environmental path. Searching in backup paths... /root/miniconda3/envs/py3.9/lib/python3.9/site-packages/bitsandbytes-0.39.0-py3.9.egg/bitsandbytes/cuda_setup/main.py:149: UserWarning: Found duplicate ['libcudart.so', 'libcudart.so.11.0', 'libcudart.so.12.0'] files: {PosixPath('/usr/local/cuda/lib64/libcudart.so'), PosixPath('/usr/local/cuda/lib64/libcudart.so.11.0')}.. We'll flip a coin and try one of these, in order to fail forward. Either way, this might cause trouble in the future: If you get `CUDA error: invalid device function` errors, the above might be the cause and the solution is to make sure only one ['libcudart.so', 'libcudart.so.11.0', 'libcudart.so.12.0'] in the paths that we search based on your env. warn(msg) CUDA SETUP: CUDA runtime path found: /usr/local/cuda/lib64/libcudart.so CUDA SETUP: Highest compute capability among GPUs detected: 8.0 CUDA SETUP: Detected CUDA version 118 CUDA SETUP: Loading binary /root/miniconda3/envs/py3.9/lib/python3.9/site-packages/bitsandbytes-0.39.0-py3.9.egg/bitsandbytes/libbitsandbytes_cuda118.so... WARNING:root:`trust_remote_code` is set to true. Please make sure that you reviewed the remote code/model. INFO:root:loading tokenizer... /content/llm-playground/models/tiiuae_falcon-40b WARNING:root:`trust_remote_code` is set to true. Please make sure that you reviewed the remote code/model. INFO:root:loading tokenizer... /content/llm-playground/models/tiiuae_falcon-40b Using bos_token, but it is not set yet. Using pad_token, but it is not set yet. Using unk_token, but it is not set yet. INFO:root:Checking for packed prepared dataset from hub... utensil/216aa4e2be3974d0a1d25d8c19db01a4 Using bos_token, but it is not set yet. Using pad_token, but it is not set yet. Using unk_token, but it is not set yet. INFO:root:Checking for packed prepared dataset from hub... utensil/216aa4e2be3974d0a1d25d8c19db01a4 Downloading readme: 100%|██████████████████████| 471/471 [00:00<00:00, 2.06MB/s] Downloading and preparing dataset None/None to /root/.cache/huggingface/datasets/utensil___parquet/utensil--216aa4e2be3974d0a1d25d8c19db01a4-be603db1612da2a9/0.0.0/14a00e99c0d15a23649d0db8944380ac81082d4b021f398733dd84f3a6c569a7... 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Subsequent calls will reuse this data. 100%|████████████████████████████████████████████| 1/1 [00:00<00:00, 234.96it/s] WARNING:datasets.builder:Found cached dataset parquet (/root/.cache/huggingface/datasets/utensil___parquet/utensil--216aa4e2be3974d0a1d25d8c19db01a4-be603db1612da2a9/0.0.0/14a00e99c0d15a23649d0db8944380ac81082d4b021f398733dd84f3a6c569a7) INFO:root:loading model and peft_config... 100%|████████████████████████████████████████████| 1/1 [00:00<00:00, 135.03it/s] INFO:root:loading model and peft_config... Loading checkpoint shards: 100%|██████████████████| 9/9 [01:20<00:00, 9.00s/it] INFO:root:converting PEFT model w/ prepare_model_for_kbit_training INFO:root:found linear modules: ['dense_4h_to_h', 'dense', 'query_key_value', 'dense_h_to_4h'] Loading checkpoint shards: 100%|██████████████████| 9/9 [01:21<00:00, 9.09s/it] INFO:root:converting PEFT model w/ prepare_model_for_kbit_training INFO:root:found linear modules: ['dense_4h_to_h', 'dense_h_to_4h', 'query_key_value', 'dense'] trainable params: 444,334,080 || all params: 21,363,310,592 || trainable%: 2.0798933671188187 INFO:torch.distributed.distributed_c10d:Added key: store_based_barrier_key:1 to store for rank: 1 trainable params: 444,334,080 || all params: 21,363,310,592 || trainable%: 2.0798933671188187 INFO:torch.distributed.distributed_c10d:Added key: store_based_barrier_key:1 to store for rank: 0 INFO:torch.distributed.distributed_c10d:Rank 0: Completed store-based barrier for key:store_based_barrier_key:1 with 2 nodes. INFO:torch.distributed.distributed_c10d:Rank 1: Completed store-based barrier for key:store_based_barrier_key:1 with 2 nodes. INFO:root:Compiling torch model INFO:root:Compiling torch model INFO:root:Pre-saving adapter config to /content/axolotl-trained/falcon-qlora-40b-minotaur/ INFO:root:Starting trainer... INFO:root:Pre-saving adapter config to /content/axolotl-trained/falcon-qlora-40b-minotaur/ INFO:root:Starting trainer... wandb: Currently logged in as: utensil. Use `wandb login --relogin` to force relogin wandb: Tracking run with wandb version 0.15.4 wandb: Run data is saved locally in /workspace/axolotl/wandb/run-20230616_071848-o4myz1ep wandb: Run `wandb offline` to turn off syncing. wandb: Syncing run twilight-wildflower-46 wandb: ⭐️ View project at https://wandb.ai/utensil/falcon-qlora wandb: 🚀 View run at https://wandb.ai/utensil/falcon-qlora/runs/o4myz1ep 0%| | 0/35325 [00:00<?, ?it/s]You're using a PreTrainedTokenizerFast tokenizer. Please note that with a fast tokenizer, using the `__call__` method is faster than using a method to encode the text followed by a call to the `pad` method to get a padded encoding. You're using a PreTrainedTokenizerFast tokenizer. Please note that with a fast tokenizer, using the `__call__` method is faster than using a method to encode the text followed by a call to the `pad` method to get a padded encoding. {'loss': 1.4081, 'learning_rate': 2e-05, 'epoch': 0.0} 0%| | 1/35325 [00:16<157:05:47, 16.01s/it]INFO:torch.nn.parallel.distributed:Reducer buckets have been rebuilt in this iteration. 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%env HF_HUB_DISABLE_PROGRESS_BARS=1
%env ACCELERATE_USE_DEEPSPEED=false
!cat examples/falcon/config-40b-qlora.yml
#%%writefile examples/falcon/config-40b-qlora.yml
!accelerate launch scripts/finetune.py examples/falcon/config-40b-qlora.yml
%cd /workspace/axolotl
%env ACCELERATE_USE_DEEPSPEED=false
%env HF_HUB_DISABLE_PROGRESS_BARS=1
!cat examples/falcon/config-40b-qlora.yml
#%%writefile examples/falcon/config-40b-qlora.yml
!accelerate launch scripts/finetune.py examples/falcon/config-40b-qlora.yml
%env HF_HUB_DISABLE_PROGRESS_BARS=1
!cat examples/falcon/config-40b-qlora.yml
!accelerate launch scripts/finetune.py examples/falcon/config-40b-qlora.yml
!cat examples/falcon/config-40b-qlora.yml
!accelerate launch scripts/finetune.py examples/falcon/config-40b-qlora.yml
!cat examples/falcon/config-40b-qlora.yml
!accelerate launch scripts/finetune.py examples/falcon/config-40b-qlora.yml --deepspeed ds_config.json
!cat examples/falcon/config-40b-qlora.yml
!accelerate launch scripts/finetune.py examples/falcon/config-40b-qlora.yml
!cat examples/falcon/config-40b-qlora.yml
!accelerate launch scripts/finetune.py examples/falcon/config-40b-qlora.yml --deepspeed ds_config.json
%cd /content/axolotl-trained/falcon-qlora-40b-gsm8k/
!ls -lhta |grep checkpoint-
!ls -lhta |grep checkpoint- | awk 'NR > 1 {print $9}'
# ls -lhta |grep checkpoint- | awk 'NR > 1 {print $9}' | xargs rm -rf
!python /workspace/llm-playground/helper/storage.py utensil/axolotl-trained /content/ -u
current out dir:
/content/axolotl-trained/falcon-qlora-40b-gsm8k/
# First interupt the kernel, wait a few seconds then run this to kill finetune to release VRAM
!ps aux|grep python|grep finetune|awk '{print $2}'|xargs kill
# Only run this to start over
!rm -rf /content/axolotl-trained/falcon-qlora-40b-gsm8k/
!apt install zip
!zip -r last_run_prepared.zip -xi last_run_prepared
# Run this in a seperate terminal
!nvitop -m full
%cd /
!du -d 2 -h|grep G
!du -d 2 -h /root/.local
!rm -rf /root/.local/share/Trash/
!rm -rf /root/.local/share/wandb/
!rm -rf /root/.cache/wandb/
!apt install lsof
!lsof /dev/nvidia*
!bash --norc --noprofile
!cd /content/axolotl-trained/falcon-qlora-40b-gsm8k/ && ls -lhta |grep checkpoint- | awk '{print $9}'
checkpoint-10
!cd /content/axolotl-trained/falcon-qlora-40b-gsm8k/ && ls -lhta |grep checkpoint- | awk 'NR > 1 {print $9}' | xargs rm -rf
#@title Keep this tab alive to prevent Colab from disconnecting you { display-mode: "form" }
#@markdown Press play on the music player that will appear below:
%%html
<audio src="https://oobabooga.github.io/silence.m4a" controls>