Instructions to use BOBsssss/gemma2-ecommerce-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BOBsssss/gemma2-ecommerce-lora with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("BOBsssss/gemma2-ecommerce-lora", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use BOBsssss/gemma2-ecommerce-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 BOBsssss/gemma2-ecommerce-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 BOBsssss/gemma2-ecommerce-lora to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for BOBsssss/gemma2-ecommerce-lora to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="BOBsssss/gemma2-ecommerce-lora", max_seq_length=2048, )
- Xet hash:
- 3720417ab727e897f3f3cb8f57044a37d2f4d3ab0df39bbe259c835174b9419e
- Size of remote file:
- 34.4 MB
- SHA256:
- 00636d529731efd619ee96a1c76d9b8d5bf73b0fd47c1646c15cce25cba37e27
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