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
- Xet hash:
- 3ce6e5782aee2f8e19750a7154acec39af0d2f5e1a9de34f97f1fefe87a8bf23
- Size of remote file:
- 443 MB
- SHA256:
- ae841d72c59f923ca8f0bb7b75381d8c2588935a3a4fffb3dc67e0947ec125d9
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