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Daniel Han-Chen 2024-06-14 20:53:51 +10:00
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@ -100,14 +100,16 @@ model = FastLanguageModel.get_peft_model(
### Conda Installation
Select either `pytorch-cuda=11.8` for CUDA 11.8 or `pytorch-cuda=12.1` for CUDA 12.1. If you have `mamba`, use `mamba` instead of `conda` for faster solving. See this [Github issue](https://github.com/unslothai/unsloth/issues/73) for help on debugging Conda installs.
```bash
conda create --name unsloth_env python=3.10
conda create --name unsloth_env \
python=3.10 \
pytorch-cuda=<11.8/12.1> \
pytorch cudatoolkit xformers -c pytorch -c nvidia -c xformers \
-y
conda activate unsloth_env
conda install pytorch-cuda=<12.1/11.8> pytorch cudatoolkit xformers -c pytorch -c nvidia -c xformers
pip install "unsloth[colab-new] @ git+https://github.com/unslothai/unsloth.git"
pip install --no-deps trl peft accelerate bitsandbytes
pip install --no-deps "trl<0.9.0" peft accelerate bitsandbytes
```
### Pip Installation
@ -162,7 +164,7 @@ pip install --no-deps packaging ninja einops flash-attn xformers trl peft accele
# Pre Ampere RTX 2080, T4, GTX 1080 GPUs:
pip install "unsloth[colab-new] @ git+https://github.com/unslothai/unsloth.git"
pip install --no-deps xformers trl peft accelerate bitsandbytes
pip install --no-deps xformers "trl<0.9.0" peft accelerate bitsandbytes
```
7. For Pytorch 2.3.0: Use the `"ampere"` path for newer RTX 30xx GPUs or higher.
```bash