Sentence Similarity
sentence-transformers
Safetensors
English
modernbert
feature-extraction
dense
Generated from Trainer
dataset_size:5749
loss:CosineSimilarityLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use johnnyboycurtis/ModernBERT-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use johnnyboycurtis/ModernBERT-small with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("johnnyboycurtis/ModernBERT-small") sentences = [ "The man is shooting an automatic rifle.", "A man is shooting a gun.", "A man is driving a car.", "A man is dancing." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from johnnyboycurtis/ModernBERT-small: direct link, hf CLI and curl.
- Browser
- Download file 3.58 MB
-
https://huggingface.co/johnnyboycurtis/ModernBERT-small/resolve/main/tokenizer.json
- Command line
-
hf download hf://johnnyboycurtis/ModernBERT-small/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/johnnyboycurtis/ModernBERT-small/resolve/main/tokenizer.json
3.58 MB
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