Sentence Similarity
sentence-transformers
PyTorch
TensorFlow
ONNX
Safetensors
OpenVINO
roberta
feature-extraction
text-embeddings-inference
Instructions to use sentence-transformers/msmarco-roberta-base-ance-firstp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use sentence-transformers/msmarco-roberta-base-ance-firstp with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("sentence-transformers/msmarco-roberta-base-ance-firstp") 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] - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 78b1f9f2e7a51903785773da8d4cd06fd48158c17eb17cf50edd2d9654c88964
- Size of remote file:
- 496 MB
- SHA256:
- e482eee056c2851a100f0939f55215955fbdb4671cb3c2d05d7d25b1fe25ece3
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