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---
title: README
emoji: ❤️
colorFrom: red
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
# 1. Load a pretrained Sentence Transformer model
model = SentenceTransformer("all-MiniLM-L6-v2")
# The sentences to encode
sentences = [
"The weather is lovely today.",
"It's so sunny outside!",
"He drove to the stadium.",
]
# 2. Calculate embeddings by calling model.encode()
embeddings = model.encode(sentences)
print(embeddings.shape)
# [3, 384]
# 3. Calculate the embedding similarities
similarities = model.similarity(embeddings, embeddings)
print(similarities)
# tensor([[1.0000, 0.6660, 0.1046],
# [0.6660, 1.0000, 0.1411],
# [0.1046, 0.1411, 1.0000]])
```
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 ❤️
<div class="grid lg:grid-cols-3 gap-x-4 gap-y-7">
<a href="https://www.sbert.net/" class="block overflow-hidden group">
<div
class="w-full h-40 object-cover mb-2 rounded-lg flex items-center justify-center bg-[#FA8072]"
>
<img alt="" src="https://huggingface.co/spaces/sentence-transformers/README/resolve/main/sbertLogo.png" class="w-40" />
</div>
<div class="underline">Documentation</div>
</a>
<a
href="https://sbert.net/docs/package_reference/SentenceTransformer.html#sentence_transformers.SentenceTransformer.push_to_hub"
class="block overflow-hidden group"
>
<div
class="w-full h-40 mb-2 bg-gray-900 group-hover:bg-gray-850 rounded-lg flex items-start justify-start overflow-hidden"
>
<img
alt=""
src="https://huggingface.co/spaces/sentence-transformers/README/resolve/main/push-to-hub.png"
class="w-full h-40 object-cover overflow-hidden"
/>
</div>
<div class="underline">Push your Sentence Transformers models to the Hub ❤️ </div>
</a>
<a
href="https://huggingface.co/models?library=sentence-transformers&sort=downloads"
class="block overflow-hidden group"
>
<div
class="w-full h-40 mb-2 bg-gray-900 group-hover:bg-gray-850 rounded-lg flex items-start justify-start overflow-hidden"
>
<img
alt=""
src="https://huggingface.co/spaces/sentence-transformers/README/resolve/main/sbert-hf.png"
class="w-full h-40 object-cover overflow-hidden"
/>
</div>
<div class="underline">Find all Sentence Transformers models on the 🤗 Hub</div>
</a>
</div>
To upload your Sentence Transformers models to the Hugging Face Hub, log in with `huggingface-cli login` and use the [`push_to_hub`](https://sbert.net/docs/package_reference/SentenceTransformer.html#sentence_transformers.SentenceTransformer.push_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.push_to_hub("my_new_model")
``` |