Sentence Similarity
sentence-transformers
Safetensors
modernbert
feature-extraction
Generated from Trainer
dataset_size:5749
loss:CosineSimilarityLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use CocoRoF/ModernBERT-SimCSE-multitask_v03-retry with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use CocoRoF/ModernBERT-SimCSE-multitask_v03-retry with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("CocoRoF/ModernBERT-SimCSE-multitask_v03-retry") sentences = [ "우리는 움직이는 동행 우주 정지 좌표계에 비례하여 이동하고 있습니다 ... 약 371km / s에서 별자리 leo 쪽으로. \"", "두 마리의 독수리가 가지에 앉는다.", "다른 물체와는 관련이 없는 '정지'는 없다.", "소녀는 버스의 열린 문 앞에 서 있다." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from CocoRoF/ModernBERT-SimCSE-multitask_v03-retry: direct link, hf CLI and curl.
- Browser
- Download file 7.58 MB
-
https://huggingface.co/CocoRoF/ModernBERT-SimCSE-multitask_v03-retry/resolve/main/tokenizer.json
- Command line
-
hf download hf://CocoRoF/ModernBERT-SimCSE-multitask_v03-retry/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/CocoRoF/ModernBERT-SimCSE-multitask_v03-retry/resolve/main/tokenizer.json
7.58 MB
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