Sentence Similarity
sentence-transformers
Safetensors
qwen3
code-retrieval
multilingual
matryoshka
custom_code
text-embeddings-inference
Instructions to use brokkai/Muninn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use brokkai/Muninn with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("brokkai/Muninn", trust_remote_code=True) 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:
- 3fd4514ef19053e125dc34112582c7fcbd29f8f5a6d32bff8ec72ac067b768ea
- Size of remote file:
- 11.4 MB
- SHA256:
- 297600527f1df1d03edf0268ebf340f551a7d5266d64cc8f1303e69390a17bfc
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