Instructions to use Joshua1702/fairrecovery-Llama-3.2-1B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Joshua1702/fairrecovery-Llama-3.2-1B with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Joshua1702/fairrecovery-Llama-3.2-1B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use Joshua1702/fairrecovery-Llama-3.2-1B with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Joshua1702/fairrecovery-Llama-3.2-1B to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for Joshua1702/fairrecovery-Llama-3.2-1B to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Joshua1702/fairrecovery-Llama-3.2-1B to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="Joshua1702/fairrecovery-Llama-3.2-1B", max_seq_length=2048, )
- Xet hash:
- 15ee80c8b5606fa0fb97c9f22c1163e0b5273e8e2cd42dd6ccec5e3430318c8d
- Size of remote file:
- 45.1 MB
- SHA256:
- 64303a8248a8f82aaa399f88ac65a3f3e679a2f9c142a314d807e7e66bf15e58
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