Instructions to use bartowski/DeepSeek-Coder-V2-Lite-Instruct-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use bartowski/DeepSeek-Coder-V2-Lite-Instruct-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="bartowski/DeepSeek-Coder-V2-Lite-Instruct-GGUF", filename="DeepSeek-Coder-V2-Lite-Instruct-IQ2_M.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use bartowski/DeepSeek-Coder-V2-Lite-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 bartowski/DeepSeek-Coder-V2-Lite-Instruct-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf bartowski/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-server -hf bartowski/DeepSeek-Coder-V2-Lite-Instruct-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf bartowski/DeepSeek-Coder-V2-Lite-Instruct-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 bartowski/DeepSeek-Coder-V2-Lite-Instruct-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf bartowski/DeepSeek-Coder-V2-Lite-Instruct-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 bartowski/DeepSeek-Coder-V2-Lite-Instruct-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf bartowski/DeepSeek-Coder-V2-Lite-Instruct-GGUF:Q4_K_M
Use Docker
docker model run hf.co/bartowski/DeepSeek-Coder-V2-Lite-Instruct-GGUF:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use bartowski/DeepSeek-Coder-V2-Lite-Instruct-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "bartowski/DeepSeek-Coder-V2-Lite-Instruct-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "bartowski/DeepSeek-Coder-V2-Lite-Instruct-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/bartowski/DeepSeek-Coder-V2-Lite-Instruct-GGUF:Q4_K_M
- Ollama
How to use bartowski/DeepSeek-Coder-V2-Lite-Instruct-GGUF with Ollama:
ollama run hf.co/bartowski/DeepSeek-Coder-V2-Lite-Instruct-GGUF:Q4_K_M
- Unsloth Studio new
How to use bartowski/DeepSeek-Coder-V2-Lite-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 bartowski/DeepSeek-Coder-V2-Lite-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 bartowski/DeepSeek-Coder-V2-Lite-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 bartowski/DeepSeek-Coder-V2-Lite-Instruct-GGUF to start chatting
- Docker Model Runner
How to use bartowski/DeepSeek-Coder-V2-Lite-Instruct-GGUF with Docker Model Runner:
docker model run hf.co/bartowski/DeepSeek-Coder-V2-Lite-Instruct-GGUF:Q4_K_M
- Lemonade
How to use bartowski/DeepSeek-Coder-V2-Lite-Instruct-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull bartowski/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
K quants should not contain IQ4_NL types inside
That breaks support for backends that don't support I-Quants
Oh I don't know why I didn't get a notification from your GitHub ping...
I think it has something to do with the shape of the tensor and not being divisible by 256
Same thing on other people's quants too:
Here's a comment from Slaren explaining when a similar thing happened with Qwen2 and my p100:
https://github.com/ggerganov/llama.cpp/issues/7805#issuecomment-2166507695
Hmm okay.
I wonder if it would be prudent to label such quants as non-K quants.
Have an I-Quanted tensor means it breaks all other backends that don't support it, while people assume it's a regular k quant and wonder why Q3_K_M works but not Q3_K_S
Never mind, ggerganov has provided an upcoming fix https://github.com/ggerganov/llama.cpp/pull/8489
A simple re-quant after this would solve the issue.
yeah it seems an odd choice to fallback to something that can be unsupported lol
glad a fix is coming..