Sentence Similarity
sentence-transformers
PyTorch
TensorFlow
Transformers
roberta
feature-extraction
Instructions to use Jainam/freeflow-biencoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use Jainam/freeflow-biencoder with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Jainam/freeflow-biencoder") 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] - Transformers
How to use Jainam/freeflow-biencoder with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Jainam/freeflow-biencoder") model = AutoModel.from_pretrained("Jainam/freeflow-biencoder", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 51b62bfa946109adf3241a150b59019e5db6f0673d53212d212b84920269f80b
- Size of remote file:
- 499 MB
- SHA256:
- afeae60c06644540514ac1137717e536b2f6701366bf2248f278fbd8e21e42cf
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