Feature Extraction
sentence-transformers
PyTorch
Safetensors
xlm-roberta
mteb
Sentence Transformers
sentence-similarity
Eval Results (legacy)
text-embeddings-inference
Instructions to use cocongy/e5-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use cocongy/e5-finetuned with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("cocongy/e5-finetuned") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7be5ca69693be86c74cacfe18a7feb7a1dae964d9d8d57c50e227c5decc81482
- Size of remote file:
- 1.11 GB
- SHA256:
- 26fb0d8dfca33b681eb3b59a553122197fc13ab81ea777a59e0529ff5df9bd0d
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