diff --git a/README.md b/README.md index cbdd3a093d..bfe7f2255b 100644 --- a/README.md +++ b/README.md @@ -168,18 +168,16 @@ pip install unsloth 6. Finally, install `bitsandbytes` and check it with `python -m bitsandbytes` ### Conda Installation (Optional) -`⚠️Only use Conda if you have it. If not, use Pip`. Select either `pytorch-cuda=11.8,12.1` for CUDA 11.8 or CUDA 12.1. We support `python=3.10,3.11,3.12`. +`⚠️Only use Conda if you have it. If not, use Pip`. We support `python=3.10,3.11,3.12,3.13`. ```bash -conda create --name unsloth_env \ - python=3.11 \ - pytorch-cuda=12.1 \ - pytorch cudatoolkit xformers -c pytorch -c nvidia -c xformers \ - -y +conda create --name unsloth_env python==3.12 -y conda activate unsloth_env - -pip install unsloth ``` - +Use `nvidia-smi` to get the correct CUDA version like 13.0 which becomes `cu130` +```bash +pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu130 +pip3 install unsloth +```
If you're looking to install Conda in a Linux environment, read here, or run the below 🔽 @@ -291,7 +289,7 @@ Access Jupyter Lab at `http://localhost:8888` and start fine-tuning! Unsloth example code to fine-tune gpt-oss-20b: ```python -from unsloth import FastLanguageModel, FastModel +from unsloth import FastLanguageModel, FastModel, FastVisionModel import torch from trl import SFTTrainer, SFTConfig from datasets import load_dataset @@ -306,9 +304,9 @@ fourbit_models = [ ] # More models at https://huggingface.co/unsloth -model, tokenizer = FastModel.from_pretrained( +model, tokenizer = FastLanguageModel.from_pretrained( model_name = "unsloth/gpt-oss-20b", - max_seq_length = 2048, # Choose any for long context! + max_seq_length = max_seq_length, # Choose any for long context! load_in_4bit = True, # 4-bit quantization. False = 16-bit LoRA. load_in_8bit = False, # 8-bit quantization load_in_16bit = False, # 16-bit LoRA