---
title: README
emoji: ❤️
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colorTo: red
sdk: static
pinned: false
---
SentenceTransformers 🤗 is a Python framework for state-of-the-art sentence, text and image embeddings. 

Install the [Sentence Transformers](https://www.sbert.net/) library.
```
pip install -U sentence-transformers
```

The usage is as simple as:
```python
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](https://www.sbert.net/) models! You can collaborate with your organization, upload and showcase your own models in your profile ❤️

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   <div class="underline">Documentation</div>
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   <div class="underline">Push your Sentence Transformers models to the Hub ❤️ </div>
</a>
<a
   href="https://huggingface.co/models?library=sentence-transformers&sort=downloads"
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   <div class="underline">Find all Sentence Transformers models on the 🤗 Hub</div>
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To upload your Sentence Transformers models to the Hugging Face Hub, log in with `huggingface-cli login` and use the [`save_to_hub`](https://sbert.net/docs/package_reference/SentenceTransformer.html#sentence_transformers.SentenceTransformer.save_to_hub) method within the Sentence Transformers library.
```python
from sentence_transformers import SentenceTransformer

# Load or train a model
model = SentenceTransformer(...)
# Push to Hub
model.save_to_hub("my_new_model")
```