Instructions to use AtomicChat/DeepSeek-V4-Flash-0731-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 AtomicChat/DeepSeek-V4-Flash-0731-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 AtomicChat/DeepSeek-V4-Flash-0731-GGUF:BF16 # Run inference directly in the terminal: llama cli -hf AtomicChat/DeepSeek-V4-Flash-0731-GGUF:BF16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf AtomicChat/DeepSeek-V4-Flash-0731-GGUF:BF16 # Run inference directly in the terminal: llama cli -hf AtomicChat/DeepSeek-V4-Flash-0731-GGUF:BF16
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 AtomicChat/DeepSeek-V4-Flash-0731-GGUF:BF16 # Run inference directly in the terminal: ./build/bin/llama cli -hf AtomicChat/DeepSeek-V4-Flash-0731-GGUF:BF16
Use Docker
docker model run hf.co/AtomicChat/DeepSeek-V4-Flash-0731-GGUF:BF16
- Llama new
- LM Studio
- Jan
- vLLM
How to use AtomicChat/DeepSeek-V4-Flash-0731-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "AtomicChat/DeepSeek-V4-Flash-0731-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": "AtomicChat/DeepSeek-V4-Flash-0731-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/AtomicChat/DeepSeek-V4-Flash-0731-GGUF:BF16
- Ollama
How to use AtomicChat/DeepSeek-V4-Flash-0731-GGUF with Ollama:
ollama run hf.co/AtomicChat/DeepSeek-V4-Flash-0731-GGUF:BF16
- Unsloth Desktop
- Pi
How to use AtomicChat/DeepSeek-V4-Flash-0731-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf AtomicChat/DeepSeek-V4-Flash-0731-GGUF:BF16
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "AtomicChat/DeepSeek-V4-Flash-0731-GGUF:BF16" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use AtomicChat/DeepSeek-V4-Flash-0731-GGUF with Docker Model Runner:
docker model run hf.co/AtomicChat/DeepSeek-V4-Flash-0731-GGUF:BF16
- Lemonade
How to use AtomicChat/DeepSeek-V4-Flash-0731-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull AtomicChat/DeepSeek-V4-Flash-0731-GGUF:BF16
Run and chat with the model
lemonade run user.DeepSeek-V4-Flash-0731-GGUF-BF16
List all available models
lemonade list
- Hermes Agent
How to use AtomicChat/DeepSeek-V4-Flash-0731-GGUF with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf AtomicChat/DeepSeek-V4-Flash-0731-GGUF:BF16
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 AtomicChat/DeepSeek-V4-Flash-0731-GGUF:BF16
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use AtomicChat/DeepSeek-V4-Flash-0731-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf AtomicChat/DeepSeek-V4-Flash-0731-GGUF:BF16
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 "AtomicChat/DeepSeek-V4-Flash-0731-GGUF:BF16" \ --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"
Does BF16 (gguf) 162 GB work with IK-llama.cpp ?
Also, does it work together with DSPARK BF16 11.3 GB? https://huggingface.co/unsloth/DeepSeek-V4-Flash-0731-GGUF
I would like to know before downloading big files.
Thank you!
Hi @MartinPatterson !
All the i/k quants that we release whould work on ik-llama.cpp, however I'm not sure if it supports DeepSeek V4 Flash 0731 itself
I can check later if you want, but it would be faster, and also greatly appreciated, if you will check it yourself :)
Currently i've only preview downloaded, and downloading 0731 is still few weeks away for me. If you are able to test it sooner with IK, please keep me updated!
Cheers!
IK llama does support DS4 and its 0731 version, DS4 has been the fork focus for a few weeks already.