Sentence Similarity
sentence-transformers
Safetensors
modernbert
feature-extraction
Generated from Trainer
dataset_size:550152
loss:CosineSimilarityLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use xgen-ai/KoModernBERT_SBERT_compare_mlmlv3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use xgen-ai/KoModernBERT_SBERT_compare_mlmlv3 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("xgen-ai/KoModernBERT_SBERT_compare_mlmlv3") sentences = [ "한 남자가 다리가 허벅지에 있고 자전거 헬멧이 두 개 뒤에 있는 여자 옆에 앉아 있다.", "그 어린 소년은 야외에서 장난감 비행기를 날리고 있었다.", "사람들은 더 잘 보기 위해 서 있다.", "남자가 여자의 허벅지에 다리를 얹고 있다." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Download modules.json from xgen-ai/KoModernBERT_SBERT_compare_mlmlv3: direct link, hf CLI and curl.
- Browser
- Download file 341 Bytes
-
https://huggingface.co/xgen-ai/KoModernBERT_SBERT_compare_mlmlv3/resolve/main/modules.json
- Command line
-
hf download hf://xgen-ai/KoModernBERT_SBERT_compare_mlmlv3/modules.json
-
curl -L -o modules.json https://huggingface.co/xgen-ai/KoModernBERT_SBERT_compare_mlmlv3/resolve/main/modules.json
341 Bytes
| [ | |
| { | |
| "idx": 0, | |
| "name": "0", | |
| "path": "", | |
| "type": "sentence_transformers.models.Transformer" | |
| }, | |
| { | |
| "idx": 1, | |
| "name": "1", | |
| "path": "1_Pooling", | |
| "type": "sentence_transformers.models.Pooling" | |
| }, | |
| { | |
| "idx": 2, | |
| "name": "2", | |
| "path": "2_Dense", | |
| "type": "sentence_transformers.models.Dense" | |
| } | |
| ] |