Instructions to use nharshavardhana/axiom-gemma-4-E2B-it_lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nharshavardhana/axiom-gemma-4-E2B-it_lora with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("nharshavardhana/axiom-gemma-4-E2B-it_lora", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use nharshavardhana/axiom-gemma-4-E2B-it_lora 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 nharshavardhana/axiom-gemma-4-E2B-it_lora 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 nharshavardhana/axiom-gemma-4-E2B-it_lora to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for nharshavardhana/axiom-gemma-4-E2B-it_lora to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="nharshavardhana/axiom-gemma-4-E2B-it_lora", max_seq_length=2048, )
- Xet hash:
- 9401975f92047cf8ef6a8d830ab15ed1507b62b24471863743a6a9c9ad14ef11
- Size of remote file:
- 32.2 MB
- SHA256:
- 254c29b0d59978a3142c584bad4e739d8d41de94be294fffcf55c8ddd92bc518
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