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
Download tf_model.h5 from sentence-transformers/msmarco-roberta-base-ance-firstp: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/sentence-transformers/msmarco-roberta-base-ance-firstp/resolve/main/tf_model.h5
- Command line
-
hf download hf://sentence-transformers/msmarco-roberta-base-ance-firstp/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/sentence-transformers/msmarco-roberta-base-ance-firstp/resolve/main/tf_model.h5
499 MB
- Xet hash:
- 4938b902934696f15992903b54eaadeb20607449eb8aa96fe3e563ea94c76e79
- Size of remote file:
- 499 MB
- SHA256:
- 8e1866fdadd59e8f5b2cfc8b970c7e0365f2b913ec10c8fb151ac359afc1e877
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