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-00002-of-00004.safetensors from r76941156/rare-disease-embedding-model: direct link, hf CLI and curl.
- Browser
- Download file 4.92 GB
-
https://huggingface.co/r76941156/rare-disease-embedding-model/resolve/main/model-00002-of-00004.safetensors
- Command line
-
hf download hf://r76941156/rare-disease-embedding-model/model-00002-of-00004.safetensors
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curl -L -o model-00002-of-00004.safetensors https://huggingface.co/r76941156/rare-disease-embedding-model/resolve/main/model-00002-of-00004.safetensors
4.92 GB
- Xet hash:
- 0522bf6db1722bb2ecb62f01078b8a3a1c7a70fe653180ddd6b214a172b34bee
- Size of remote file:
- 4.92 GB
- SHA256:
- f12968bfea36f0684bc4fa3f0a8d96dd8671785273d4e99f30d037d0fa963e57
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