Instructions to use haboussiCodes/Gemma_arabic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use haboussiCodes/Gemma_arabic with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("haboussiCodes/Gemma_arabic", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use haboussiCodes/Gemma_arabic 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 haboussiCodes/Gemma_arabic 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 haboussiCodes/Gemma_arabic to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for haboussiCodes/Gemma_arabic to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="haboussiCodes/Gemma_arabic", max_seq_length=2048, )
- Xet hash:
- 2d49a9467056f73d499c13ac9e532aee1ca396e1586089a281ebae9f45d05c0d
- Size of remote file:
- 200 MB
- SHA256:
- 5705a14458200e9ce7fada5aecb28d1b642ed45eb1bb26055aa01e2e3d3ace68
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