Sentence Similarity
sentence-transformers
Safetensors
English
bert
feature-extraction
patent
embeddings
mteb
text-embeddings-inference
Instructions to use datalyes/patembed-large_no_prompts with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use datalyes/patembed-large_no_prompts with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("datalyes/patembed-large_no_prompts") 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 tokenizer.json from datalyes/patembed-large_no_prompts: direct link, hf CLI and curl.
- Browser
- Download file 959 kB
-
https://huggingface.co/datalyes/patembed-large_no_prompts/resolve/main/tokenizer.json
- Command line
-
hf download hf://datalyes/patembed-large_no_prompts/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/datalyes/patembed-large_no_prompts/resolve/main/tokenizer.json
959 kB
File too large to display, you can check the raw version instead.