Instructions to use mad-lab-ai/deepseek-coder-v2-lite-instruct-GGUF 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 mad-lab-ai/deepseek-coder-v2-lite-instruct-GGUF 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 mad-lab-ai/deepseek-coder-v2-lite-instruct-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf mad-lab-ai/deepseek-coder-v2-lite-instruct-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf mad-lab-ai/deepseek-coder-v2-lite-instruct-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf mad-lab-ai/deepseek-coder-v2-lite-instruct-GGUF:Q4_K_M
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf mad-lab-ai/deepseek-coder-v2-lite-instruct-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf mad-lab-ai/deepseek-coder-v2-lite-instruct-GGUF:Q4_K_M
Use Docker
docker model run hf.co/mad-lab-ai/deepseek-coder-v2-lite-instruct-GGUF:Q4_K_M
- Llama new
- LM Studio
- Jan
- Ollama
How to use mad-lab-ai/deepseek-coder-v2-lite-instruct-GGUF with Ollama:
ollama run hf.co/mad-lab-ai/deepseek-coder-v2-lite-instruct-GGUF:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use mad-lab-ai/deepseek-coder-v2-lite-instruct-GGUF with Docker Model Runner:
docker model run hf.co/mad-lab-ai/deepseek-coder-v2-lite-instruct-GGUF:Q4_K_M
- Lemonade
How to use mad-lab-ai/deepseek-coder-v2-lite-instruct-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull mad-lab-ai/deepseek-coder-v2-lite-instruct-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.deepseek-coder-v2-lite-instruct-GGUF-Q4_K_M
List all available models
lemonade list
- Atomic Chat
DeepSeek-Coder-V2-Lite-Instruct-GGUF
GGUF quantizations of DeepSeek-Coder-V2-Lite-Instruct with imatrix calibration for improved accuracy at lower bit depths.
Available Quants
| Quant | Size | Use Case |
|---|---|---|
| Q6_K | ~13GB | Best quality, high VRAM |
| Q5_K_M | ~11GB | Recommended balance |
| Q4_K_M | ~9GB | Low VRAM / fast inference |
All quants use imatrix calibration data for better perplexity vs. standard quants.
Usage
Load with llama.cpp, Ollama, LM Studio, or any GGUF-compatible runtime.
Original Model
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Model tree for mad-lab-ai/deepseek-coder-v2-lite-instruct-GGUF
Base model
deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct