Instructions to use bylang/doctor-gemma3-4b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bylang/doctor-gemma3-4b with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("bylang/doctor-gemma3-4b", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use bylang/doctor-gemma3-4b 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 bylang/doctor-gemma3-4b 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 bylang/doctor-gemma3-4b to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for bylang/doctor-gemma3-4b to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="bylang/doctor-gemma3-4b", max_seq_length=2048, )
- Xet hash:
- 7a1376cb0edae6686b6e67e28e5393a28abee6e6a3471e7512895483bd2273a3
- Size of remote file:
- 4.96 GB
- SHA256:
- 2ebab670e55efca9d6a7149e8e8ac826393fb88eef874a6a8cb2a972c9953c68
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