Feature Extraction
Transformers
Safetensors
chest2vec_embedding
text-embeddings
retrieval
radiology
chest
qwen
custom_code
Instructions to use lukeingawesome/chest2vec_0.6b_chest with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lukeingawesome/chest2vec_0.6b_chest with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="lukeingawesome/chest2vec_0.6b_chest", trust_remote_code=True, device_map="auto")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("lukeingawesome/chest2vec_0.6b_chest", trust_remote_code=True, dtype="auto", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Merge remote changes, keep simplified global-embeddings-only model 2bea063
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Simplify model to global embeddings only (no section pooling), update adapter weights from resume3 checkpoint-11270 999f0c9
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Update adapter weights from checkpoint-11270 cc78f26
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Initial release: chest2vec_0.6b_chest c6f3f7a
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