Instructions to use Austin9/gemma-2-2b-it-Ko-QCR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Austin9/gemma-2-2b-it-Ko-QCR with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Austin9/gemma-2-2b-it-Ko-QCR", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use Austin9/gemma-2-2b-it-Ko-QCR 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 Austin9/gemma-2-2b-it-Ko-QCR 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 Austin9/gemma-2-2b-it-Ko-QCR to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Austin9/gemma-2-2b-it-Ko-QCR to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="Austin9/gemma-2-2b-it-Ko-QCR", max_seq_length=2048, )
- Xet hash:
- 0c7ee4706346a4d0b351b850819cce14f0d9ab9d73d1641dd371f91d6174b3d6
- Size of remote file:
- 83.1 MB
- SHA256:
- 509969f252f72134f273c9030e3fa39d572a4745906d91c73169a04845602a29
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