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FloatDo/exaone-4.0-1.2b-float-right-tagger-GGUF
exaone-4.0-1.2b-float-right-tagger-GGUF is a machine learning model from FloatDo. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for llama.cpp. The card lists the license as other.
GGUF builds for EXAONE-4.0-1.2B Float:Right Tagger.
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From the Hugging Face model README
GGUF builds for EXAONE-4.0-1.2B Float:Right Tagger.
This model is tuned to output tags as a JSON array for short Korean text inputs.
non-GGUF : https://huggingface.co/FloatDo/exaone-4.0-1.2b-float-right-tagger
exaone-4.0-1.2b-float-right-tagger.f16.gguf (FP16)exaone-4.0-1.2b-float-right-tagger.Q8_0.ggufexaone-4.0-1.2b-float-right-tagger.Q4_K_M.gguf ✅ recommended (often outputs clean tags with less extra text)Example:
llama-cli -m exaone-4.0-1.2b-float-right-tagger.Q4_K_M.gguf -n 96 -t 8 --temp 0 \
-p $'너는 태그 생성기다. 반드시 JSON 배열만 출력한다. 다른 글자 금지.\n\
규칙:\n- 태그 3~10개\n- 너무 디테일하지 않게(큰 주제)\n- 언더스코어(_) 금지\n\n\
문장:\n직장 상사가 계속 야근을 시켜서 스트레스 받는다. 퇴사 고민 중.\n\nassistant:\n'
Expected output (example):
["직장","스트레스","퇴사","상사","일자리"]
Notes • For stricter JSON-only behavior, use --temp 0 and keep -n small (64~96).