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sentence-transformers/gooaq
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sentence-transformers/yahoo-answers
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sentence-transformers/msmarco-msmarco-distilbert-base-tas-b
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sentence-transformers/msmarco-msmarco-distilbert-base-v3
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Sentence Transformers
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AI & ML interests
In the following you find models tuned to be used for sentence / text embedding generation. They can be used with the sentence-transformers package.
Recent Activity
Organization Card
SentenceTransformers 🤗 is a Python framework for state-of-the-art sentence, text and image embeddings.
Install the Sentence Transformers library.
pip install -U sentence-transformers
The usage is as simple as:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer('paraphrase-MiniLM-L6-v2')
# Sentences we want to encode. Example:
sentence = ['This framework generates embeddings for each input sentence']
# Sentences are encoded by calling model.encode()
embedding = model.encode(sentence)
Hugging Face makes it easy to collaboratively build and showcase your Sentence Transformers models! You can collaborate with your organization, upload and showcase your own models in your profile ❤️
Documentation
Push your Sentence Transformers models to the Hub ❤️
Find all Sentence Transformers models on the 🤗 Hub
To upload your Sentence Transformers models to the Hugging Face Hub, log in with huggingface-cli login
and use the save_to_hub
method within the Sentence Transformers library.
from sentence_transformers import SentenceTransformer
# Load or train a model
model = SentenceTransformer(...)
# Push to Hub
model.push_to_hub("my_new_model")
Collections
3
A curated subset of the datasets that work out of the box with Sentence Transformers: https://huggingface.co/datasets?other=sentence-transformers
These datasets all have "english" and "non_english" columns for numerous datasets. They can be used to make embedding models multilingual.
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sentence-transformers/parallel-sentences-wikititles
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sentence-transformers/parallel-sentences-tatoeba
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sentence-transformers/parallel-sentences-talks
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sentence-transformers/parallel-sentences-europarl
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sentence-transformers/xlm-r-base-en-ko-nli-ststb
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sentence-transformers/bert-base-wikipedia-sections-mean-tokens
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sentence-transformers/bert-base-nli-cls-token
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sentence-transformers/all-MiniLM-L12-v1
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sentence-transformers/all-MiniLM-L6-v1
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sentence-transformers/all-mpnet-base-v1
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sentence-transformers/facebook-dpr-ctx_encoder-multiset-base
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sentence-transformers/facebook-dpr-ctx_encoder-single-nq-base
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sentence-transformers/facebook-dpr-question_encoder-multiset-base
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sentence-transformers/facebook-dpr-question_encoder-single-nq-base
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sentence-transformers/msmarco-hard-negatives
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sentence-transformers/parallel-sentences
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sentence-transformers/embedding-training-data
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sentence-transformers/parallel-sentences-opus-100
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sentence-transformers/trivia-qa-triplet
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sentence-transformers/t2ranking
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sentence-transformers/mr-tydi
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sentence-transformers/miracl
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sentence-transformers/mldr
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sentence-transformers/pubmedqa
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