Text Classification
Transformers
Safetensors
Korean
roberta
DPR
Classification
RAG
text-embeddings-inference
Instructions to use NHNDQ/SelectionModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NHNDQ/SelectionModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="NHNDQ/SelectionModel")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("NHNDQ/SelectionModel") model = AutoModelForSequenceClassification.from_pretrained("NHNDQ/SelectionModel") - Notebooks
- Google Colab
- Kaggle
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- RAG
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## Model Details
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* Model Description:
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* Developed by: Jisu Kim, TakSung Heo, Minsu Jeong, and Juhwan Lee
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* Model Type: Classification
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* License: CC-BY-4.0
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- RAG
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## Model Details
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* Model Description: Selection Model
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* Developed by: Jisu Kim, TakSung Heo, Minsu Jeong, and Juhwan Lee
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* Model Type: Classification
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* License: CC-BY-4.0
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