Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
text-embeddings-inference
Instructions to use josejointriple/model_21 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use josejointriple/model_21 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("josejointriple/model_21") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Download config_sentence_transformers.json from josejointriple/model_21: direct link, hf CLI and curl.
- Browser
- Download file 172 Bytes
-
https://huggingface.co/josejointriple/model_21/resolve/main/config_sentence_transformers.json
- Command line
-
hf download hf://josejointriple/model_21/config_sentence_transformers.json
-
curl -L -o config_sentence_transformers.json https://huggingface.co/josejointriple/model_21/resolve/main/config_sentence_transformers.json
172 Bytes
| { | |
| "__version__": { | |
| "sentence_transformers": "2.2.2", | |
| "transformers": "4.28.1", | |
| "pytorch": "1.13.0+cu117" | |
| }, | |
| "prompts": {}, | |
| "default_prompt_name": null | |
| } |