Instructions to use Matjac5/document_encoder_07_06old with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Matjac5/document_encoder_07_06old with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Matjac5/document_encoder_07_06old") 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 model.safetensors from Matjac5/document_encoder_07_06old: direct link, hf CLI and curl.
- Browser
- Download file 436 MB
-
https://huggingface.co/Matjac5/document_encoder_07_06old/resolve/main/model.safetensors
- Command line
-
hf download hf://Matjac5/document_encoder_07_06old/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/Matjac5/document_encoder_07_06old/resolve/main/model.safetensors
436 MB
- Xet hash:
- 51f5123e467b5809ee7b9dbc9dc107831c4abdcf150f6b8d2a4dadcdc88e594a
- Size of remote file:
- 436 MB
- SHA256:
- a322942dfd35a8578a8fb3921dc2b2764770d7fcfa4063b506154069b2ee4bef
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