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Update GPTQ-models-(4-bit-mode).md
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@ -37,7 +37,29 @@ Different branches of GPTQ-for-LLaMa are currently available, including:
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Overall, I recommend using the old CUDA branch. It is included by default in the one-click-installer for this web UI.
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### Installation using precompiled wheels
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### Installation
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Start by cloning GPTQ-for-LLaMa into your `text-generation-webui/repositories` folder:
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```
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mkdir repositories
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cd repositories
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git clone https://github.com/oobabooga/GPTQ-for-LLaMa.git -b cuda
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```
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If you want to you to use the up-to-date CUDA or triton branches instead of the old CUDA branch, use these commands:
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```
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git clone https://github.com/qwopqwop200/GPTQ-for-LLaMa.git -b cuda
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```
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```
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git clone https://github.com/qwopqwop200/GPTQ-for-LLaMa.git -b triton
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```
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Next you need to install the CUDA extensions. You can do that either by installing the precompiled wheels, or by compiling the wheels yourself.
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### Precompiled wheels
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Kindly provided by our friend jllllll: https://github.com/jllllll/GPTQ-for-LLaMa-Wheels
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@ -53,10 +75,9 @@ Linux:
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pip install https://github.com/jllllll/GPTQ-for-LLaMa-Wheels/raw/Linux-x64/quant_cuda-0.0.0-cp310-cp310-linux_x86_64.whl
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```
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### Manual installation
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#### Step 0: install nvcc
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#### Step 1: install nvcc
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```
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conda activate textgen
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@ -65,49 +86,25 @@ conda install -c conda-forge cudatoolkit-dev
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The command above takes some 10 minutes to run and shows no progress bar or updates along the way.
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See this issue for more details: https://github.com/oobabooga/text-generation-webui/issues/416#issuecomment-1475078571
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You are going to need to have a C++ compiler installed. On Linux, `sudo apt install build-essential` or equivalent is enough.
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#### Step 1: install GPTQ-for-LLaMa
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If you're using an older version of CUDA toolkit (e.g. 11.7) but the latest version of `gcc` and `g++` (12.0+), you should downgrade with: `conda install -c conda-forge gxx==11.3.0`. Kernel compilation will fail otherwise.
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Clone the GPTQ-for-LLaMa repository into the `text-generation-webui/repositories` subfolder and install it:
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#### Step 2: compile the CUDA extensions
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```
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mkdir repositories
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cd repositories
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git clone https://github.com/oobabooga/GPTQ-for-LLaMa.git -b cuda
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cd GPTQ-for-LLaMa
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cd repositories/GPTQ-for-LLaMa
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python setup_cuda.py install
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```
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>If you're using an older version of CUDA toolkit (e.g. 11.7) but the latest version of `gcc` and `g++` (12.0+), you should downgrade with: `conda install -c conda-forge gxx==11.3.0`. Kernel compilation will fail otherwise.
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You are going to need to have a C++ compiler installed into your system for the last command. On Linux, `sudo apt install build-essential` or equivalent is enough.
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If you want to you to use the up-to-date CUDA or triton branches instead of the old CUDA branch, use these commands:
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```
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cd repositories
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rm -r GPTQ-for-LLaMa
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pip uninstall -y quant-cuda
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git clone https://github.com/qwopqwop200/GPTQ-for-LLaMa.git -b cuda
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...
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```
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```
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cd repositories
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rm -r GPTQ-for-LLaMa
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pip uninstall -y quant-cuda
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git clone https://github.com/qwopqwop200/GPTQ-for-LLaMa.git -b triton
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...
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```
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#### Step 2: get the pre-converted weights
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### Pre-converted weights
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* Converted without `group-size` (better for the 7b model): https://github.com/oobabooga/text-generation-webui/pull/530#issuecomment-1483891617
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* Converted with `group-size` (better from 13b upwards): https://github.com/oobabooga/text-generation-webui/pull/530#issuecomment-1483941105
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⚠️ The tokenizer files in the sources above may be outdated. Make sure to obtain the universal LLaMA tokenizer as described [here](https://github.com/oobabooga/text-generation-webui/blob/main/docs/LLaMA-model.md#option-1-pre-converted-weights).
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#### Step 3: Start the web UI:
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### Starting the web UI:
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For the models converted without `group-size`:
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