Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
text-embeddings-inference
Instructions to use danfeg/IF-E5-L_Finetuned-COMB-12481 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use danfeg/IF-E5-L_Finetuned-COMB-12481 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("danfeg/IF-E5-L_Finetuned-COMB-12481") 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/IF-E5-L_Finetuned-COMB-12481: direct link, hf CLI and curl.
- Browser
- Download file 1.34 GB
-
https://huggingface.co/danfeg/IF-E5-L_Finetuned-COMB-12481/resolve/main/model.safetensors
- Command line
-
hf download hf://danfeg/IF-E5-L_Finetuned-COMB-12481/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/danfeg/IF-E5-L_Finetuned-COMB-12481/resolve/main/model.safetensors
1.34 GB
- Xet hash:
- 1f842709fec795c87988cbb08d4e2199bdfb984433adee70b8decf25c28cf300
- Size of remote file:
- 1.34 GB
- SHA256:
- 286132d0a17a261e7317b760235e2d9c77fb09a80ec02d6bda970da85cea62a2
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