Sentence Similarity
sentence-transformers
PyTorch
bloom
feature-extraction
mteb
Eval Results (legacy)
Instructions to use bigscience/sgpt-bloom-7b1-msmarco with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use bigscience/sgpt-bloom-7b1-msmarco with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("bigscience/sgpt-bloom-7b1-msmarco") 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/sgpt-bloom-7b1-msmarco: direct link, hf CLI and curl.
- Browser
- Download file 14.5 MB
-
https://huggingface.co/bigscience/sgpt-bloom-7b1-msmarco/resolve/main/tokenizer.json
- Command line
-
hf download hf://bigscience/sgpt-bloom-7b1-msmarco/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/bigscience/sgpt-bloom-7b1-msmarco/resolve/main/tokenizer.json
14.5 MB
- Xet hash:
- 174095779cf3e20b84792558d798924005212dd66b40463082e062b5fbdd6df6
- Size of remote file:
- 14.5 MB
- SHA256:
- 53b546fa3c6b32936b8e411c6b0c98c66fa272b0e69d1bb025b0026b1908e930
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