Spaces:
Running
Running
| 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 | |
| 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 ❤️ | |
| <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.save_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 [`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.push_to_hub("my_new_model") | |
| ``` |