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Quantized Retrieval
Efficient quantized retrieval over Wikipedia
In the following you find models tuned to be used for sentence / text embedding generation. They can be used with the sentence-transformers package.
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 ❤️
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.save_to_hub("my_new_model")