Instructions to use vulcan2506/llama3-medmcqa-1-instructv2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vulcan2506/llama3-medmcqa-1-instructv2 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("vulcan2506/llama3-medmcqa-1-instructv2", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use vulcan2506/llama3-medmcqa-1-instructv2 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 vulcan2506/llama3-medmcqa-1-instructv2 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 vulcan2506/llama3-medmcqa-1-instructv2 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for vulcan2506/llama3-medmcqa-1-instructv2 to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="vulcan2506/llama3-medmcqa-1-instructv2", max_seq_length=2048, )
- Xet hash:
- 0a0f00173c09121bb31b887d30339ef4312eb10c61bb07d4df4bfdcdfd1dd1e3
- Size of remote file:
- 6.87 kB
- SHA256:
- 9ee30db3ddc1cb909797e8bbe7ffa8fbe26b16f289ef95a66ab95be64f57bbbd
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