Sentence Similarity
sentence-transformers
Safetensors
modernbert
semantic-similarity
representlm
text-embeddings-inference
Instructions to use suproteem/RepresentLM-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use suproteem/RepresentLM-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("suproteem/RepresentLM-v2") 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 2_Normalize/.gitattributes from suproteem/RepresentLM-v2: direct link, hf CLI and curl.
- Browser
- Download file 0 Bytes
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https://huggingface.co/suproteem/RepresentLM-v2/resolve/main/2_Normalize/.gitattributes
- Command line
-
hf download hf://suproteem/RepresentLM-v2/2_Normalize/.gitattributes
-
curl -L -o .gitattributes https://huggingface.co/suproteem/RepresentLM-v2/resolve/main/2_Normalize/.gitattributes
0 Bytes