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:
- 23b8666a3869675112f3125b9e0d2c45a1e9707b29e5ab83cd74eab79b9504c8
- Size of remote file:
- 2.36 MB
- SHA256:
- 74b35ef522b16d7ad53b338b3bd6448545446bb0a23a2dbbccdfe3e3baa2ae10
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.