Sentence Similarity
sentence-transformers
Safetensors
qwen3
embedding
biomedical
rare-disease
phenotype
retrieval
text-embeddings-inference
Instructions to use r76941156/rare-disease-embedding-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use r76941156/rare-disease-embedding-model with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("r76941156/rare-disease-embedding-model") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Download model-00001-of-00004.safetensors from r76941156/rare-disease-embedding-model: direct link, hf CLI and curl.
- Browser
- Download file 4.9 GB
-
https://huggingface.co/r76941156/rare-disease-embedding-model/resolve/1e0db890e6416807d1832b26ef959b6707d8508d/model-00001-of-00004.safetensors
- Command line
-
hf download hf://r76941156/rare-disease-embedding-model@1e0db890e6416807d1832b26ef959b6707d8508d/model-00001-of-00004.safetensors
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curl -L -o model-00001-of-00004.safetensors https://huggingface.co/r76941156/rare-disease-embedding-model/resolve/1e0db890e6416807d1832b26ef959b6707d8508d/model-00001-of-00004.safetensors
4.9 GB
- Xet hash:
- d0bd885b18eed8807141f6e2ece3d9d8a3cc607351f7a9348a5c5a3c898a6a15
- Size of remote file:
- 4.9 GB
- SHA256:
- c8008e8911ea388876103a4ba87891d397504e82fbf06bd52dc12739d4eef343
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