Sentence Similarity
sentence-transformers
Safetensors
mpnet
feature-extraction
text-embeddings-inference
Instructions to use danfeg/ST-ALL-MPNET_Finetuned-COMB-1500 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use danfeg/ST-ALL-MPNET_Finetuned-COMB-1500 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("danfeg/ST-ALL-MPNET_Finetuned-COMB-1500") 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 model.safetensors from danfeg/ST-ALL-MPNET_Finetuned-COMB-1500: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/danfeg/ST-ALL-MPNET_Finetuned-COMB-1500/resolve/c9c5b4370e9eba8a8f92eacb840756f8fc237528/model.safetensors
- Command line
-
hf download hf://danfeg/ST-ALL-MPNET_Finetuned-COMB-1500@c9c5b4370e9eba8a8f92eacb840756f8fc237528/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/danfeg/ST-ALL-MPNET_Finetuned-COMB-1500/resolve/c9c5b4370e9eba8a8f92eacb840756f8fc237528/model.safetensors
438 MB
- Xet hash:
- 2f4a5b30c9a12b3e93664d4219f119149f25b92cfd01cce95744479616a46fd0
- Size of remote file:
- 438 MB
- SHA256:
- 300c4dfac28891391b311651fe44acf02d812ed7e527366ea7b7e0698eb8af7b
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