Instructions to use terrancl/gemma_3_4b-wolf_numbers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use terrancl/gemma_3_4b-wolf_numbers with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("terrancl/gemma_3_4b-wolf_numbers", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Unsloth Studio new
How to use terrancl/gemma_3_4b-wolf_numbers 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 terrancl/gemma_3_4b-wolf_numbers 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 terrancl/gemma_3_4b-wolf_numbers to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for terrancl/gemma_3_4b-wolf_numbers to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="terrancl/gemma_3_4b-wolf_numbers", max_seq_length=2048, )
- Xet hash:
- cabda31e2f7f0a1fc02053ba529f645bdcb1da6d2c1fac8868a8f444e0432f77
- Size of remote file:
- 33.4 MB
- SHA256:
- 4447cd9317dd6e123d570a8ff1866a785ac012a05d5eb046efb4203411f28019
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