Sentence Similarity
sentence-transformers
PyTorch
roberta
feature-extraction
text-embeddings-inference
Instructions to use ncoop57/codeformer-java with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use ncoop57/codeformer-java with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ncoop57/codeformer-java") 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 ncoop57/codeformer-java: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/ncoop57/codeformer-java/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ncoop57/codeformer-java/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ncoop57/codeformer-java/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- 8768d8b7773c8e46024b278c39239923bdb664d81614ec542c6a20aa3e28e4b9
- Size of remote file:
- 499 MB
- SHA256:
- 9a5cefdac3bc73a3594dc32faf749f08773a4189f881d245531a9798d513125b
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