Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
text-embeddings-inference
Instructions to use danfeg/IF-E5-L_Finetuned-COMB-7443 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-7443 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("danfeg/IF-E5-L_Finetuned-COMB-7443") 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-7443: direct link, hf CLI and curl.
- Browser
- Download file 1.34 GB
-
https://huggingface.co/danfeg/IF-E5-L_Finetuned-COMB-7443/resolve/main/model.safetensors
- Command line
-
hf download hf://danfeg/IF-E5-L_Finetuned-COMB-7443/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/danfeg/IF-E5-L_Finetuned-COMB-7443/resolve/main/model.safetensors
1.34 GB
- Xet hash:
- 631188e53d9cb68b26c9f991c126e0536bcb9896c517c9b8f8c61a605212437b
- Size of remote file:
- 1.34 GB
- SHA256:
- 50599fefcfcef17df38c9a0aecbf377672b1aebe03ae555d1d80a50b2e1e0d59
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