Sentence Similarity
sentence-transformers
Safetensors
roberta
embeddings
code
solidity
ethereum
smart-contracts
security
text-embeddings-inference
Instructions to use software-ses/RavenBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use software-ses/RavenBERT with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("software-ses/RavenBERT") 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
- Xet hash:
- 17bec155818cf3a6a7b6f7586ee729153b7b3441b886d3c9452a1bd4d91ee93d
- Size of remote file:
- 499 MB
- SHA256:
- 94da241dca4733f0ee5f227f8ca84181013675d49a77e701c21ff8b917c656bb
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