Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
dense
Generated from Trainer
dataset_size:4555
loss:MultipleNegativesRankingLoss
text-embeddings-inference
Instructions to use SSHHIVANI/verifact-biencoder-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use SSHHIVANI/verifact-biencoder-v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("SSHHIVANI/verifact-biencoder-v1") sentences = [ "Shahid Kapoor was in a film.", "In addition to acting in films , Kapoor has sung several of her film songs .", "Two years later , he played a drug abusing singer in the crime drama Udta Punjab , which won him the Filmfare Critics Award for Best Actor .", "Matthew Paige Damon -LRB- -LSB- ˈdeɪmən -RSB- born October 8 , 1970 -RRB- is an American actor , film producer , and screenwriter ." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
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