Instructions to use BrianGITS/gemma-3-4b-medicalCOT-sft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BrianGITS/gemma-3-4b-medicalCOT-sft with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("BrianGITS/gemma-3-4b-medicalCOT-sft", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download adapter_model.safetensors from BrianGITS/gemma-3-4b-medicalCOT-sft: direct link, hf CLI and curl.
- Browser
- Download file 262 MB
-
https://huggingface.co/BrianGITS/gemma-3-4b-medicalCOT-sft/resolve/main/adapter_model.safetensors
- Command line
-
hf download hf://BrianGITS/gemma-3-4b-medicalCOT-sft/adapter_model.safetensors
-
curl -L -o adapter_model.safetensors https://huggingface.co/BrianGITS/gemma-3-4b-medicalCOT-sft/resolve/main/adapter_model.safetensors
262 MB
- Xet hash:
- 279505d582bba0ecc1f88c5e7bc6cded0303125378dd5189a86842908545fcc2
- Size of remote file:
- 262 MB
- SHA256:
- cb067eb8d2843bc275ff4e71dc0113fe583145d40066454388018a96cbb8979d
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