Sentence Similarity
sentence-transformers
Safetensors
English
new
feature-extraction
loss:MultipleNegativesRankingLoss
custom_code
text-embeddings-inference
Instructions to use mathreader/stella_en_400M_v5_finetuned_embedding_scorer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use mathreader/stella_en_400M_v5_finetuned_embedding_scorer with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("mathreader/stella_en_400M_v5_finetuned_embedding_scorer", trust_remote_code=True) 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
Welcome to the community
The community tab is the place to discuss and collaborate with the HF community!