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-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use michaelfeil/ct2fast-e5-large-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("michaelfeil/ct2fast-e5-large-v2") 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 ·
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Parent(s): 6a2a1fd
Upload intfloat/e5-large-v2 ctranslate fp16 weights
Browse files
README.md
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```
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```
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ct2-transformers-converter --model intfloat/e5-large-v2 --output_dir ~/tmp-ct2fast-e5-large-v2 --force --copy_files tokenizer.json README.md tokenizer_config.json vocab.txt special_tokens_map.json .gitattributes --quantization
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```
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Checkpoint compatible to [ctranslate2>=3.16.0](https://github.com/OpenNMT/CTranslate2)
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```
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ct2-transformers-converter --model intfloat/e5-large-v2 --output_dir ~/tmp-ct2fast-e5-large-v2 --force --copy_files tokenizer.json README.md tokenizer_config.json vocab.txt special_tokens_map.json .gitattributes --quantization float16 --trust_remote_code
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```
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Checkpoint compatible to [ctranslate2>=3.16.0](https://github.com/OpenNMT/CTranslate2)
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model.bin
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