Instructions to use johnt/bert_ft_sentence with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use johnt/bert_ft_sentence with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("johnt/bert_ft_sentence") 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 pytorch_model.bin from johnt/bert_ft_sentence: direct link, hf CLI and curl.
- Browser
- Download file 90.9 MB
-
https://huggingface.co/johnt/bert_ft_sentence/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://johnt/bert_ft_sentence/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/johnt/bert_ft_sentence/resolve/main/pytorch_model.bin
90.9 MB
- Xet hash:
- 4f9bf0a054739b07e50cc041a140a0ac10c6610d85c28ba8a393f074ab20e8da
- Size of remote file:
- 90.9 MB
- SHA256:
- 1a2205ed8ebfddd6c43f4dde1e0fdeeaf70395351b27c20522555d56f5951f8b
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