Instructions to use unsloth/Kimi-K2-Instruct-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use unsloth/Kimi-K2-Instruct-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("unsloth/Kimi-K2-Instruct-GGUF", dtype="auto") - llama-cpp-python
How to use unsloth/Kimi-K2-Instruct-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="unsloth/Kimi-K2-Instruct-GGUF", filename="BF16/Kimi-K2-Instruct-BF16-00001-of-00045.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 unsloth/Kimi-K2-Instruct-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf unsloth/Kimi-K2-Instruct-GGUF:UD-Q4_K_XL # Run inference directly in the terminal: llama-cli -hf unsloth/Kimi-K2-Instruct-GGUF:UD-Q4_K_XL
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf unsloth/Kimi-K2-Instruct-GGUF:UD-Q4_K_XL # Run inference directly in the terminal: llama-cli -hf unsloth/Kimi-K2-Instruct-GGUF:UD-Q4_K_XL
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 unsloth/Kimi-K2-Instruct-GGUF:UD-Q4_K_XL # Run inference directly in the terminal: ./llama-cli -hf unsloth/Kimi-K2-Instruct-GGUF:UD-Q4_K_XL
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 unsloth/Kimi-K2-Instruct-GGUF:UD-Q4_K_XL # Run inference directly in the terminal: ./build/bin/llama-cli -hf unsloth/Kimi-K2-Instruct-GGUF:UD-Q4_K_XL
Use Docker
docker model run hf.co/unsloth/Kimi-K2-Instruct-GGUF:UD-Q4_K_XL
- LM Studio
- Jan
- Ollama
How to use unsloth/Kimi-K2-Instruct-GGUF with Ollama:
ollama run hf.co/unsloth/Kimi-K2-Instruct-GGUF:UD-Q4_K_XL
- Unsloth Studio
How to use unsloth/Kimi-K2-Instruct-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 unsloth/Kimi-K2-Instruct-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 unsloth/Kimi-K2-Instruct-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for unsloth/Kimi-K2-Instruct-GGUF to start chatting
- Pi
How to use unsloth/Kimi-K2-Instruct-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama-server -hf unsloth/Kimi-K2-Instruct-GGUF:UD-Q4_K_XL
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": "unsloth/Kimi-K2-Instruct-GGUF:UD-Q4_K_XL" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use unsloth/Kimi-K2-Instruct-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 unsloth/Kimi-K2-Instruct-GGUF:UD-Q4_K_XL
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 unsloth/Kimi-K2-Instruct-GGUF:UD-Q4_K_XL
Run Hermes
hermes
- Docker Model Runner
How to use unsloth/Kimi-K2-Instruct-GGUF with Docker Model Runner:
docker model run hf.co/unsloth/Kimi-K2-Instruct-GGUF:UD-Q4_K_XL
- Lemonade
How to use unsloth/Kimi-K2-Instruct-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull unsloth/Kimi-K2-Instruct-GGUF:UD-Q4_K_XL
Run and chat with the model
lemonade run user.Kimi-K2-Instruct-GGUF-UD-Q4_K_XL
List all available models
lemonade list
Upload folder using huggingface_hub
Browse files
README.md
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tags:
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base_model:
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license: other
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<img src="figures/kimi-logo.png" width="30%" alt="Kimi K2: Open Agentic Intellignece">
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tags:
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base_model:
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license: other
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> [!NOTE]
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> Includes our **chat template fixes**! <br> For `llama.cpp`, use `--jinja`
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<em><a href="https://docs.unsloth.ai/basics/unsloth-dynamic-v2.0-gguf">Unsloth Dynamic 2.0</a> achieves superior accuracy & outperforms other leading quants.</em>
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<a href="https://discord.gg/unsloth">
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<a href="https://docs.unsloth.ai/">
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<img src="figures/kimi-logo.png" width="30%" alt="Kimi K2: Open Agentic Intellignece">
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