Sentence Similarity
sentence-transformers
Safetensors
xlm-roberta
feature-extraction
dense
Generated from Trainer
dataset_size:43318
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Instructions to use leewonjun/e5-mul-0910a with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use leewonjun/e5-mul-0910a with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("leewonjun/e5-mul-0910a") sentences = [ "query: 3PL 사용 시의 비용 절감 메커니즘은 어떤 것이 있나요?", "passage: 3 Dimension-Through Silicon Via (Technical)", "passage: Third Party Logistics (상업)", "passage: Authorization Account Answer (Technical)" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Notebooks
- Google Colab
- Kaggle
Download config.json from leewonjun/e5-mul-0910a: direct link, hf CLI and curl.
- Browser
- Download file 657 Bytes
-
https://huggingface.co/leewonjun/e5-mul-0910a/resolve/main/config.json
- Command line
-
hf download hf://leewonjun/e5-mul-0910a/config.json
-
curl -L -o config.json https://huggingface.co/leewonjun/e5-mul-0910a/resolve/main/config.json
657 Bytes
| { | |
| "architectures": [ | |
| "XLMRobertaModel" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "bos_token_id": 0, | |
| "classifier_dropout": null, | |
| "dtype": "float32", | |
| "eos_token_id": 2, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 1024, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 4096, | |
| "layer_norm_eps": 1e-05, | |
| "max_position_embeddings": 514, | |
| "model_type": "xlm-roberta", | |
| "num_attention_heads": 16, | |
| "num_hidden_layers": 24, | |
| "output_past": true, | |
| "pad_token_id": 1, | |
| "position_embedding_type": "absolute", | |
| "transformers_version": "4.56.1", | |
| "type_vocab_size": 1, | |
| "use_cache": true, | |
| "vocab_size": 250002 | |
| } | |