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
Download tokenizer.json from ThakiCloud/EvidenceLink-DART-Reranker-KO: direct link, hf CLI and curl.
- Browser
- Download file 17.1 MB
-
https://huggingface.co/ThakiCloud/EvidenceLink-DART-Reranker-KO/resolve/main/tokenizer.json
- Command line
-
hf download hf://ThakiCloud/EvidenceLink-DART-Reranker-KO/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/ThakiCloud/EvidenceLink-DART-Reranker-KO/resolve/main/tokenizer.json
17.1 MB
- Xet hash:
- 8609cedc690486f3066b1c41147e9660283f785434f1cdfefb96e120d782e4f2
- Size of remote file:
- 17.1 MB
- SHA256:
- 425a292ab98dcc4731590fa00c2f177e450476e147aeab40db4061b4e38ba25a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.