Text Classification
Transformers
Safetensors
Korean
xlm-roberta
reranker
cross-encoder
dart
opendart
financial-disclosure
korean
record-linkage
convertible-bond
text-embeddings-inference
Instructions to use ThakiCloud/EvidenceLink-DART-Reranker-KO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ThakiCloud/EvidenceLink-DART-Reranker-KO with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ThakiCloud/EvidenceLink-DART-Reranker-KO")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ThakiCloud/EvidenceLink-DART-Reranker-KO") model = AutoModelForSequenceClassification.from_pretrained("ThakiCloud/EvidenceLink-DART-Reranker-KO", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 408 Bytes
039683c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | {
"add_prefix_space": true,
"backend": "tokenizers",
"bos_token": "<s>",
"clean_up_tokenization_spaces": true,
"cls_token": "<s>",
"eos_token": "</s>",
"is_local": true,
"local_files_only": false,
"mask_token": "<mask>",
"model_max_length": 8192,
"pad_token": "<pad>",
"sep_token": "</s>",
"sp_model_kwargs": {},
"tokenizer_class": "XLMRobertaTokenizer",
"unk_token": "<unk>"
}
|