Feature Extraction
Transformers
Safetensors
chest2vec
text-embeddings
retrieval
radiology
chest
qwen
custom_code
Instructions to use chest2vec/chest2vec_4B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chest2vec/chest2vec_4B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="chest2vec/chest2vec_4B", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("chest2vec/chest2vec_4B", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download .gitignore from chest2vec/chest2vec_4B: direct link, hf CLI and curl.
- Browser
- Download file 193 Bytes
-
https://huggingface.co/chest2vec/chest2vec_4B/resolve/main/.gitignore
- Command line
-
hf download hf://chest2vec/chest2vec_4B/.gitignore
-
curl -L -o .gitignore https://huggingface.co/chest2vec/chest2vec_4B/resolve/main/.gitignore
193 Bytes
| # Build artifacts | |
| dist/ | |
| build/ | |
| *.egg-info/ | |
| __pycache__/ | |
| *.pyc | |
| *.pyo | |
| *.pyd | |
| .Python | |
| # Testing | |
| .pytest_cache/ | |
| .coverage | |
| htmlcov/ | |
| # IDE | |
| .vscode/ | |
| .idea/ | |
| *.swp | |
| *.swo | |
| # Jupyter | |
| .ipynb_checkpoints/ | |