Auto-Vicuna
Fast Chat and transformers must be installed via requirements file for now.
Installing PyTorch and NVIDIA dependencies
First, upgrade wheel and friends.
pip install --upgrade setuptools pip wheel
For CUDA 11.X:
pip install nvidia-cuda-runtime-cu11 --index-url https://pypi.ngc.nvidia.com
For CUDA 12.x
pip install nvidia-cuda-runtime-cu12 --index-url https://pypi.ngc.nvidia.com
For PyTorch cu117
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu117
For PyTorch cu118
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
You might need to add:
--upgrade --force-reinstall
To the PyTorch installation commands if you have a previous version of PyTorch installed.
LLaMA Weights
If your weights used LLaMATokenizer you may need a different version of transformers.
I have fork that should work located here: https://github.com/BillSchumacher/transformers
You should clone this repo and:
pip uninstall transformers
cd path/to/my/transformers/cloned/repo
python setup.py install
For some reason pip install -e . causes issues.
If you do that, delete pycache, dist and build folders and try the setup.py method instead.
Google Colab
Interactive manual
Check out the: InteractiveManual.ipynb
For a Jupyter notebook guide.
Metadata
Release files for auto-vicuna 0.2.1
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| File | Size | Uploaded | Provenance | Actions |
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Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
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| auto_vicuna-0.2.1-py3-none-any.whl | Python 3 | none | any | Details for auto_vicuna-0.2.1-py3-none-any.whl |
Total release size: 23.9 kB
Release files / auto_vicuna-0.2.1.tar.gz
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| Tags | Python 3 |
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