Instructions to use FloatDo/exaone-4.0-1.2b-float-right-tagger-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use FloatDo/exaone-4.0-1.2b-float-right-tagger-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="FloatDo/exaone-4.0-1.2b-float-right-tagger-GGUF", filename="exaone-4.0-1.2b-float-right-tagger.Q4_K_M.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use FloatDo/exaone-4.0-1.2b-float-right-tagger-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf FloatDo/exaone-4.0-1.2b-float-right-tagger-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf FloatDo/exaone-4.0-1.2b-float-right-tagger-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf FloatDo/exaone-4.0-1.2b-float-right-tagger-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf FloatDo/exaone-4.0-1.2b-float-right-tagger-GGUF:Q4_K_M
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf FloatDo/exaone-4.0-1.2b-float-right-tagger-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf FloatDo/exaone-4.0-1.2b-float-right-tagger-GGUF:Q4_K_M
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf FloatDo/exaone-4.0-1.2b-float-right-tagger-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf FloatDo/exaone-4.0-1.2b-float-right-tagger-GGUF:Q4_K_M
Use Docker
docker model run hf.co/FloatDo/exaone-4.0-1.2b-float-right-tagger-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use FloatDo/exaone-4.0-1.2b-float-right-tagger-GGUF with Ollama:
ollama run hf.co/FloatDo/exaone-4.0-1.2b-float-right-tagger-GGUF:Q4_K_M
- Unsloth Studio
How to use FloatDo/exaone-4.0-1.2b-float-right-tagger-GGUF with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for FloatDo/exaone-4.0-1.2b-float-right-tagger-GGUF to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for FloatDo/exaone-4.0-1.2b-float-right-tagger-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for FloatDo/exaone-4.0-1.2b-float-right-tagger-GGUF to start chatting
- Pi
How to use FloatDo/exaone-4.0-1.2b-float-right-tagger-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf FloatDo/exaone-4.0-1.2b-float-right-tagger-GGUF:Q4_K_M
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "FloatDo/exaone-4.0-1.2b-float-right-tagger-GGUF:Q4_K_M" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use FloatDo/exaone-4.0-1.2b-float-right-tagger-GGUF with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf FloatDo/exaone-4.0-1.2b-float-right-tagger-GGUF:Q4_K_M
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default FloatDo/exaone-4.0-1.2b-float-right-tagger-GGUF:Q4_K_M
Run Hermes
hermes
- Docker Model Runner
How to use FloatDo/exaone-4.0-1.2b-float-right-tagger-GGUF with Docker Model Runner:
docker model run hf.co/FloatDo/exaone-4.0-1.2b-float-right-tagger-GGUF:Q4_K_M
- Lemonade
How to use FloatDo/exaone-4.0-1.2b-float-right-tagger-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull FloatDo/exaone-4.0-1.2b-float-right-tagger-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.exaone-4.0-1.2b-float-right-tagger-GGUF-Q4_K_M
List all available models
lemonade list
Upload GGUF builds (F16/Q8_0/Q4_K_M) + README
Browse files
.gitattributes
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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exaone-4.0-1.2b-float-right-tagger.Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
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exaone-4.0-1.2b-float-right-tagger.Q8_0.gguf filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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license: apache-2.0
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language:
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- ko
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library_name: llama.cpp
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tags:
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- gguf
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- exaone
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- tagger
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- float-right
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---
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# EXAONE-4.0-1.2B Float:Right Tagger (GGUF)
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GGUF builds for **EXAONE-4.0-1.2B Float:Right Tagger**.
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This model is tuned to output **tags as a JSON array** for short Korean text inputs.
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## Files
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- `exaone-4.0-1.2b-float-right-tagger.f16.gguf` (FP16)
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- `exaone-4.0-1.2b-float-right-tagger.Q8_0.gguf`
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- `exaone-4.0-1.2b-float-right-tagger.Q4_K_M.gguf` โ
recommended (often outputs clean tags with less extra text)
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## Prompt format (llama.cpp)
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Example:
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```bash
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llama-cli -m exaone-4.0-1.2b-float-right-tagger.Q4_K_M.gguf -n 96 -t 8 --temp 0 \
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-p $'๋๋ ํ๊ทธ ์์ฑ๊ธฐ๋ค. ๋ฐ๋์ JSON ๋ฐฐ์ด๋ง ์ถ๋ ฅํ๋ค. ๋ค๋ฅธ ๊ธ์ ๊ธ์ง.\n\
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๊ท์น:\n- ํ๊ทธ 3~10๊ฐ\n- ๋๋ฌด ๋ํ
์ผํ์ง ์๊ฒ(ํฐ ์ฃผ์ )\n- ์ธ๋์ค์ฝ์ด(_) ๊ธ์ง\n\n\
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๋ฌธ์ฅ:\n์ง์ฅ ์์ฌ๊ฐ ๊ณ์ ์ผ๊ทผ์ ์์ผ์ ์คํธ๋ ์ค ๋ฐ๋๋ค. ํด์ฌ ๊ณ ๋ฏผ ์ค.\n\nassistant:\n'
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```
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Expected output (example):
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```json
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["์ง์ฅ","์คํธ๋ ์ค","ํด์ฌ","์์ฌ","์ผ์๋ฆฌ"]
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```
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Notes
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โข For stricter JSON-only behavior, use --temp 0 and keep -n small (64~96).
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exaone-4.0-1.2b-float-right-tagger.Q4_K_M.gguf
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version https://git-lfs.github.com/spec/v1
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oid sha256:4e1cb83fcb80ceac5c8f4abd442733978830c94b355b7b267b7ebaddf03033ee
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size 812438112
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exaone-4.0-1.2b-float-right-tagger.Q8_0.gguf
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version https://git-lfs.github.com/spec/v1
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size 1363939936
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exaone-4.0-1.2b-float-right-tagger.f16.gguf
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version https://git-lfs.github.com/spec/v1
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oid sha256:8636dc13e6b633d05311a34162b0923ea25dfaaad3e4209da90dc87753e6b8f1
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size 2563248736
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