
Sentence Transformers
Research 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.
Team members 2
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 then use the save_to_hub
function within the Sentence Transformers library.
from sentence_transformers import save_to_hub save_to_hub(repo_name = 'cool_new_model')
spaces
1
models
124

sentence-transformers/all-mpnet-base-v2

sentence-transformers/sentence-t5-base

sentence-transformers/paraphrase-albert-small-v2

sentence-transformers/all-distilroberta-v1

sentence-transformers/all-MiniLM-L12-v2

sentence-transformers/distiluse-base-multilingual-cased

sentence-transformers/multi-qa-MiniLM-L6-cos-v1

sentence-transformers/distilroberta-base-msmarco-v1

sentence-transformers/nli-bert-large-cls-pooling
