Sentence Similarity
sentence-transformers
English
bert
ctranslate2
int8
float16
mteb
Sentence Transformers
Eval Results (legacy)
text-embeddings-inference
Instructions to use michaelfeil/ct2fast-e5-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use michaelfeil/ct2fast-e5-large with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("michaelfeil/ct2fast-e5-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
Commit ·
3d2a1cf
1
Parent(s): 7f77418
Upload intfloat/e5-large ctranslate fp16 weights
Browse files
README.md
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ct2-transformers-converter --model intfloat/e5-large --output_dir ~/tmp-ct2fast-e5-large --force --copy_files tokenizer.json
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```
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# Licence and other remarks:
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ct2-transformers-converter --model intfloat/e5-large --output_dir ~/tmp-ct2fast-e5-large --force --copy_files tokenizer.json modules.json README.md tokenizer_config.json sentence_bert_config.json vocab.txt special_tokens_map.json .gitattributes --trust_remote_code
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```
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# Licence and other remarks:
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