Feature Extraction
sentence-transformers
Safetensors
bert
sentence-similarity
biomedical
embeddings
life-sciences
scientific-text
SODA-VEC
EMBO
text-embeddings-inference
Instructions to use EMBO/negative_sampling_pmb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use EMBO/negative_sampling_pmb with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("EMBO/negative_sampling_pmb") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 413346cca8f816ac139e13bdb8ab370e9c995f55fd3309c2375ba966274b80c9
- Size of remote file:
- 438 MB
- SHA256:
- f0c2603d7a4399ed5d6f355d5b5624d59ba3674767c0623bc806bdb016856d81
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