Sentence Similarity
sentence-transformers
Safetensors
modernbert
feature-extraction
Generated from Trainer
dataset_size:449904
loss:CosineSimilarityLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use CocoRoF/ModernBERT-SimCSE-multitask_v05 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use CocoRoF/ModernBERT-SimCSE-multitask_v05 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("CocoRoF/ModernBERT-SimCSE-multitask_v05") 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 last-checkpoint/optimizer.pt from CocoRoF/ModernBERT-SimCSE-multitask_v05: direct link, hf CLI and curl.
- Browser
- Download file 1.23 GB
-
https://huggingface.co/CocoRoF/ModernBERT-SimCSE-multitask_v05/resolve/main/last-checkpoint/optimizer.pt
- Command line
-
hf download hf://CocoRoF/ModernBERT-SimCSE-multitask_v05/last-checkpoint/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/CocoRoF/ModernBERT-SimCSE-multitask_v05/resolve/main/last-checkpoint/optimizer.pt
1.23 GB
- Xet hash:
- 332eab5eb241c69b8a2f955008912914f4c501abe975e47aed11a9fc3fd6397a
- Size of remote file:
- 1.23 GB
- SHA256:
- f66fa8d3c164f862f611a6715d94383ebe8cf33bb65807628e137d39ceb12af2
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