Sentence Similarity
sentence-transformers
PyTorch
English
roberta
feature-extraction
text-embeddings-inference
Instructions to use flax-sentence-embeddings/all_datasets_v3_roberta-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use flax-sentence-embeddings/all_datasets_v3_roberta-large with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("flax-sentence-embeddings/all_datasets_v3_roberta-large") 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] - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from flax-sentence-embeddings/all_datasets_v3_roberta-large: direct link, hf CLI and curl.
- Browser
- Download file 1.42 GB
-
https://huggingface.co/flax-sentence-embeddings/all_datasets_v3_roberta-large/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://flax-sentence-embeddings/all_datasets_v3_roberta-large/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/flax-sentence-embeddings/all_datasets_v3_roberta-large/resolve/main/pytorch_model.bin
1.42 GB
- Xet hash:
- e9c423dd87571cf9703c0293110ac9faa3970beab228125c2eae42acdc402cb4
- Size of remote file:
- 1.42 GB
- SHA256:
- 29bb8f3e407eaaa38e2675111fa56cf6f56cb56aab4f2257477fbb1467c07747
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