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
Download tokenizer.json from bigscience-data/sgpt-bloom-1b7-nli: direct link, hf CLI and curl.
- Browser
- Download file 14.5 MB
-
https://huggingface.co/bigscience-data/sgpt-bloom-1b7-nli/resolve/main/tokenizer.json
- Command line
-
hf download hf://bigscience-data/sgpt-bloom-1b7-nli/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/bigscience-data/sgpt-bloom-1b7-nli/resolve/main/tokenizer.json
14.5 MB
- Xet hash:
- e28c7b9bbef25e2da5fc257692ba629fba1034fdf355e9d83f452a67463f6345
- Size of remote file:
- 14.5 MB
- SHA256:
- 4ab8d6865d6043895799adce910945c14ad5f54737d618dbefbe85e84d1a3436
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