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 model.safetensors from ncoop57/codeformer-java: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/ncoop57/codeformer-java/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://ncoop57/codeformer-java@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/ncoop57/codeformer-java/resolve/refs%2Fpr%2F1/model.safetensors
499 MB
- Xet hash:
- 82950a5b534c2a01b525e74d96e7406a782bddb87bd7c566d1903f44a280ebbf
- Size of remote file:
- 499 MB
- SHA256:
- b4f0970a91e363a03c0e264e497ac40ac37bcf31542338fdf3a2457895ee72bd
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