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
ncoop57 commited on
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a7dd858
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Parent(s): 25cff45
Add model
Browse files- config.json +1 -0
- pytorch_model.bin +3 -0
config.json
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{"model_name": "microsoft/codebert-base", "max_seq_length": 256}
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:b5d6b58bc04768576f98463d3e28f3a7d42187bab15cd8513f09e0556f3802fa
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size 498674551
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