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:
- ab545e0ff14907c71ca9a8ade2cf85c1eae05f8e46a1b985d961f93cf06dd73e
- Size of remote file:
- 7.14 kB
- SHA256:
- 236c1ec98a4ff4a5d3b5d0486159caa175e5b659cbdf009a04dee80f96c07cc4
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.