Sentence Similarity
sentence-transformers
Safetensors
modernbert
feature-extraction
dense
text-embeddings-inference
Instructions to use mykor/mmBERT-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use mykor/mmBERT-small with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("mykor/mmBERT-small") 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 tokenizer.json from mykor/mmBERT-small: direct link, hf CLI and curl.
- Browser
- Download file 34.4 MB
-
https://huggingface.co/mykor/mmBERT-small/resolve/main/tokenizer.json
- Command line
-
hf download hf://mykor/mmBERT-small/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/mykor/mmBERT-small/resolve/main/tokenizer.json
34.4 MB
- Xet hash:
- 8fdbdb0307b65058d3b81a88cba0082cd1bbe8e85d34295d2271d6fa85a31c7a
- Size of remote file:
- 34.4 MB
- SHA256:
- 609d8f4c067cd3950f88594c5a802616cea245823836ef5848ee4fc40aab5b6f
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