Instructions to use thejaminator/medium_high-medical-4e-05-16000-mcq0-qwen_no_reason with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thejaminator/medium_high-medical-4e-05-16000-mcq0-qwen_no_reason with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("thejaminator/medium_high-medical-4e-05-16000-mcq0-qwen_no_reason", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use thejaminator/medium_high-medical-4e-05-16000-mcq0-qwen_no_reason 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 thejaminator/medium_high-medical-4e-05-16000-mcq0-qwen_no_reason 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 thejaminator/medium_high-medical-4e-05-16000-mcq0-qwen_no_reason to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for thejaminator/medium_high-medical-4e-05-16000-mcq0-qwen_no_reason to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="thejaminator/medium_high-medical-4e-05-16000-mcq0-qwen_no_reason", max_seq_length=2048, )
- Xet hash:
- 07e8648141d252f3c9cf63225f9d1998ceb35ccd9bde968bd0df69c97b8ab62f
- Size of remote file:
- 1.07 GB
- SHA256:
- 1a2761223b65cf4cc96cc740c426543b11b5e44f549f938a74fe3d5b96a2ed95
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