Instructions to use aired/gemma-3-270m-it-python-coder-unsloth with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aired/gemma-3-270m-it-python-coder-unsloth with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("aired/gemma-3-270m-it-python-coder-unsloth", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Unsloth Studio new
How to use aired/gemma-3-270m-it-python-coder-unsloth 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 aired/gemma-3-270m-it-python-coder-unsloth 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 aired/gemma-3-270m-it-python-coder-unsloth to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for aired/gemma-3-270m-it-python-coder-unsloth to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="aired/gemma-3-270m-it-python-coder-unsloth", max_seq_length=2048, )
- Xet hash:
- 5468ac5eb4d4a27f08b9531ba383e16f7836b4d1c75061299bee1fd84ac26ef3
- Size of remote file:
- 122 MB
- SHA256:
- 4e77a98730669f8bd81ad16941c6fb6146d8e3579a01c2d05e259ccc6aacb09a
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