Instructions to use lmstudio-community/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 lmstudio-community/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="lmstudio-community/DeepSeek-Coder-V2-Lite-Instruct-GGUF", filename="DeepSeek-Coder-V2-Lite-Instruct-IQ3_M.gguf", )
llm.create_chat_completion( messages = [ { "role": "user", "content": "What is the capital of France?" } ] ) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use lmstudio-community/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 lmstudio-community/DeepSeek-Coder-V2-Lite-Instruct-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf lmstudio-community/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 lmstudio-community/DeepSeek-Coder-V2-Lite-Instruct-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf lmstudio-community/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 lmstudio-community/DeepSeek-Coder-V2-Lite-Instruct-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf lmstudio-community/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 lmstudio-community/DeepSeek-Coder-V2-Lite-Instruct-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf lmstudio-community/DeepSeek-Coder-V2-Lite-Instruct-GGUF:Q4_K_M
Use Docker
docker model run hf.co/lmstudio-community/DeepSeek-Coder-V2-Lite-Instruct-GGUF:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use lmstudio-community/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 "lmstudio-community/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": "lmstudio-community/DeepSeek-Coder-V2-Lite-Instruct-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/lmstudio-community/DeepSeek-Coder-V2-Lite-Instruct-GGUF:Q4_K_M
- Ollama
How to use lmstudio-community/DeepSeek-Coder-V2-Lite-Instruct-GGUF with Ollama:
ollama run hf.co/lmstudio-community/DeepSeek-Coder-V2-Lite-Instruct-GGUF:Q4_K_M
- Unsloth Studio
How to use lmstudio-community/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 lmstudio-community/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 lmstudio-community/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 lmstudio-community/DeepSeek-Coder-V2-Lite-Instruct-GGUF to start chatting
- Atomic Chat new
- Docker Model Runner
How to use lmstudio-community/DeepSeek-Coder-V2-Lite-Instruct-GGUF with Docker Model Runner:
docker model run hf.co/lmstudio-community/DeepSeek-Coder-V2-Lite-Instruct-GGUF:Q4_K_M
- Lemonade
How to use lmstudio-community/DeepSeek-Coder-V2-Lite-Instruct-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull lmstudio-community/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
Problem with LLM Studio
Problem with LLM Studio.
From time to time, the model stops generating text and generates something like this:
";BF*#627F,B)E-A88;&"D%+8(82:7=<C*&;;G%-2>)9.G#6+"/=846,*%)!!(#&)FC>9&%H5464H'85%;:D>@GBE@"##E1F,D@DEB--)1!/4A,9<$911=5D&<("A;/(#6C"*2;"$8/E/9D!-8!*1**54E-@D$7#<#=)86A*)E*B/1943$5;G6+04D!2119!,2>.+(#86.1B>A2-98;2"H-F<5#G1A,9D*!.+'+:$'2!C(&'794F"%D6+B4+2/#'+-(F-$/:;D(#*3G.'=&-0G'%E<8@6!83:C:93H.-0(-@D(GH%$7D&):244#;30=-E%4('%6+7!8=663E/(8><G9($84..."
Maybe stop strings issues?
I had similar issues with other models and usually the issue was stop strings.
please share the ones you have set.
I'll check it out, thanks.
Also try out the built in template, I've heard conflicting reports about the proper template (official one I've described in the card, but people have had better luck with the old one defined in the lmstudio presets)
I am also getting similar responses, regardless of template it seems :/
The same happened to me right now.
