Sentence Similarity
sentence-transformers
PyTorch
Safetensors
bloom
feature-extraction
mteb
Eval Results (legacy)
Instructions to use bigscience-data/sgpt-bloom-1b7-nli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use bigscience-data/sgpt-bloom-1b7-nli with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("bigscience-data/sgpt-bloom-1b7-nli") 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
- Xet hash:
- dd47336e5c19d91f6a721cdf8cd37318c0a35604b7ff5ca370a4255e7843b1eb
- Size of remote file:
- 6.89 GB
- SHA256:
- 5e880c3f13ae9a2912d4077266ac000c9611eebcc1123814d4af63a02a7edb72
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