Instructions to use junwoo77/jungpt1.1beta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use junwoo77/jungpt1.1beta with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf junwoo77/jungpt1.1beta # Run inference directly in the terminal: llama cli -hf junwoo77/jungpt1.1beta
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf junwoo77/jungpt1.1beta # Run inference directly in the terminal: llama cli -hf junwoo77/jungpt1.1beta
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 junwoo77/jungpt1.1beta # Run inference directly in the terminal: ./llama-cli -hf junwoo77/jungpt1.1beta
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 junwoo77/jungpt1.1beta # Run inference directly in the terminal: ./build/bin/llama-cli -hf junwoo77/jungpt1.1beta
Use Docker
docker model run hf.co/junwoo77/jungpt1.1beta
- LM Studio
- Jan
- Ollama
How to use junwoo77/jungpt1.1beta with Ollama:
ollama run hf.co/junwoo77/jungpt1.1beta
- Unsloth Studio
How to use junwoo77/jungpt1.1beta 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 junwoo77/jungpt1.1beta 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 junwoo77/jungpt1.1beta to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for junwoo77/jungpt1.1beta to start chatting
- Pi
How to use junwoo77/jungpt1.1beta with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf junwoo77/jungpt1.1beta
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": "junwoo77/jungpt1.1beta" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use junwoo77/jungpt1.1beta with Docker Model Runner:
docker model run hf.co/junwoo77/jungpt1.1beta
- Lemonade
How to use junwoo77/jungpt1.1beta with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull junwoo77/jungpt1.1beta
Run and chat with the model
lemonade run user.jungpt1.1beta-{{QUANT_TAG}}List all available models
lemonade list
- Hermes Agent
How to use junwoo77/jungpt1.1beta with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf junwoo77/jungpt1.1beta
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 junwoo77/jungpt1.1beta
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use junwoo77/jungpt1.1beta with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf junwoo77/jungpt1.1beta
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "junwoo77/jungpt1.1beta" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
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Check out the documentation for more information.
JUNGPT 1.1 Beta
ํ๊ตญ์ด ๋ํํ ๊ฐ์ธ AI JUNGPT์ ๋๋ค.
๋ชจ๋ธ ์ ๋ณด
- ๋ชจ๋ธ๋ช : JUNGPT 1.1 Beta
- Base Model: Kanana-2-3B-Instruct
- Fine-tuning: LoRA / SFT
- ์ธ์ด: ํ๊ตญ์ด ์ค์ฌ
- ํฌ๋งท: GGUF
- ์์ํ: Q4_K_M
- ํ์ผ ํฌ๊ธฐ: ์ฝ 2.1GB
- ์ํ: Beta
ํน์ง
- ํ๊ตญ์ด ์ผ์ ๋ํ
- ์ผ๋ฐ์ ์ธ ์ง๋ฌธ๊ณผ ๋ต๋ณ
- ์ฝ๋ฉ ๋ฐ ๊ฐ๋ฐ ๊ด๋ จ ์ง๋ฌธ
- ๋ก์ปฌ ํ๊ฒฝ์์ ์คํ ๊ฐ๋ฅ
- Ollama ๋ฐ llama.cpp ๋ฑ GGUF ์ง์ ํ๊ฒฝ์์ ์ฌ์ฉ ๊ฐ๋ฅ
Ollama ์ฌ์ฉ
GGUF ๋ชจ๋ธ์ ๋ค์ด๋ก๋ํ ํ Modelfile์ ์์ฑํ์ฌ Ollama์์ ์ฌ์ฉํ ์ ์์ต๋๋ค.
์์:
FROM ./jungpt1.1beta.gguf
PARAMETER temperature 0.7
PARAMETER top_p 0.9
PARAMETER num_ctx 8192
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