Text Classification
Transformers
Safetensors
exaone4
text-generation
exaone
lora
finetune
korean
tagger
Instructions to use FloatDo/exaone-4.0-1.2b-float-right-tagger with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FloatDo/exaone-4.0-1.2b-float-right-tagger with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="FloatDo/exaone-4.0-1.2b-float-right-tagger")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("FloatDo/exaone-4.0-1.2b-float-right-tagger") model = AutoModelForCausalLM.from_pretrained("FloatDo/exaone-4.0-1.2b-float-right-tagger") - Notebooks
- Google Colab
- Kaggle
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The model is designed to output **a JSON array of 3–10 high-level tags** for a given Korean sentence.
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## Intended Behavior
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Given an input sentence, the model should output **ONLY** a JSON array:
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The model is designed to output **a JSON array of 3–10 high-level tags** for a given Korean sentence.
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GGUF : https://huggingface.co/FloatDo/exaone-4.0-1.2b-float-right-tagger-GGUF
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## Intended Behavior
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Given an input sentence, the model should output **ONLY** a JSON array:
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