mirror of
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5d1018495f
* feat(intel): add diffusers support * try to consume upstream container image * Debug * Manually install deps * Map transformers/hf cache dir to modelpath if not specified * fix(compel): update initialization, pass by all gRPC options * fix: add dependencies, implement transformers for xpu * base it from the oneapi image * Add pillow * set threads if specified when launching the API * Skip conda install if intel * defaults to non-intel * ci: add to pipelines * prepare compel only if enabled * Skip conda install if intel * fix cleanup * Disable compel by default * Install torch 2.1.0 with Intel * Skip conda on some setups * Detect python * Quiet output * Do not override system python with conda * Prefer python3 * Fixups * exllama2: do not install without conda (overrides pytorch version) * exllama/exllama2: do not install if not using cuda * Add missing dataset dependency * Small fixups, symlink to python, add requirements * Add neural_speed to the deps * correctly handle model offloading * fix: device_map == xpu * go back at calling python, fixed at dockerfile level * Exllama2 restricted to only nvidia gpus * Tokenizer to xpu |
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.. | ||
autogptq | ||
bark | ||
common-env/transformers | ||
coqui | ||
diffusers | ||
exllama | ||
exllama2 | ||
mamba | ||
petals | ||
sentencetransformers | ||
transformers | ||
transformers-musicgen | ||
vall-e-x | ||
vllm | ||
README.md |
Common commands about conda environment
Create a new empty conda environment
conda create --name <env-name> python=<your version> -y
conda create --name autogptq python=3.11 -y
To activate the environment
As of conda 4.4
conda activate autogptq
The conda version older than 4.4
source activate autogptq
Install the packages to your environment
Sometimes you need to install the packages from the conda-forge channel
By using conda
conda install <your-package-name>
conda install -c conda-forge <your package-name>
Or by using pip
pip install <your-package-name>