Instructions to use JuanGondu/shipft_llama3_IT_2ep_r512_tbs2x4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JuanGondu/shipft_llama3_IT_2ep_r512_tbs2x4 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("JuanGondu/shipft_llama3_IT_2ep_r512_tbs2x4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download adapter_model.safetensors from JuanGondu/shipft_llama3_IT_2ep_r512_tbs2x4: direct link, hf CLI and curl.
- Browser
- Download file 5.37 GB
-
https://huggingface.co/JuanGondu/shipft_llama3_IT_2ep_r512_tbs2x4/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://JuanGondu/shipft_llama3_IT_2ep_r512_tbs2x4/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/JuanGondu/shipft_llama3_IT_2ep_r512_tbs2x4/resolve/main/adapter_model.safetensors
5.37 GB
- Xet hash:
- 747081cf397957bf54bc3ae36be70b06637345669ccbd4288d24a52d03f69b95
- Size of remote file:
- 5.37 GB
- SHA256:
- 3027f204ffaf1431323e0145281d9f237271946ab0e059c3a47888c9a85dbdd1
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