Instructions to use julianmb/DeepSeek-V4-Flash-0731-IQ2XXS-STRIX 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 julianmb/DeepSeek-V4-Flash-0731-IQ2XXS-STRIX 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 julianmb/DeepSeek-V4-Flash-0731-IQ2XXS-STRIX # Run inference directly in the terminal: llama cli -hf julianmb/DeepSeek-V4-Flash-0731-IQ2XXS-STRIX
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf julianmb/DeepSeek-V4-Flash-0731-IQ2XXS-STRIX # Run inference directly in the terminal: llama cli -hf julianmb/DeepSeek-V4-Flash-0731-IQ2XXS-STRIX
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 julianmb/DeepSeek-V4-Flash-0731-IQ2XXS-STRIX # Run inference directly in the terminal: ./llama-cli -hf julianmb/DeepSeek-V4-Flash-0731-IQ2XXS-STRIX
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 julianmb/DeepSeek-V4-Flash-0731-IQ2XXS-STRIX # Run inference directly in the terminal: ./build/bin/llama-cli -hf julianmb/DeepSeek-V4-Flash-0731-IQ2XXS-STRIX
Use Docker
docker model run hf.co/julianmb/DeepSeek-V4-Flash-0731-IQ2XXS-STRIX
- LM Studio
- Jan
- vLLM
How to use julianmb/DeepSeek-V4-Flash-0731-IQ2XXS-STRIX with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "julianmb/DeepSeek-V4-Flash-0731-IQ2XXS-STRIX" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "julianmb/DeepSeek-V4-Flash-0731-IQ2XXS-STRIX", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/julianmb/DeepSeek-V4-Flash-0731-IQ2XXS-STRIX
- Ollama
How to use julianmb/DeepSeek-V4-Flash-0731-IQ2XXS-STRIX with Ollama:
ollama run hf.co/julianmb/DeepSeek-V4-Flash-0731-IQ2XXS-STRIX
- Unsloth Desktop
- Pi
How to use julianmb/DeepSeek-V4-Flash-0731-IQ2XXS-STRIX with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf julianmb/DeepSeek-V4-Flash-0731-IQ2XXS-STRIX
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": "julianmb/DeepSeek-V4-Flash-0731-IQ2XXS-STRIX" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use julianmb/DeepSeek-V4-Flash-0731-IQ2XXS-STRIX with Docker Model Runner:
docker model run hf.co/julianmb/DeepSeek-V4-Flash-0731-IQ2XXS-STRIX
- Lemonade
How to use julianmb/DeepSeek-V4-Flash-0731-IQ2XXS-STRIX with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull julianmb/DeepSeek-V4-Flash-0731-IQ2XXS-STRIX
Run and chat with the model
lemonade run user.DeepSeek-V4-Flash-0731-IQ2XXS-STRIX-{{QUANT_TAG}}List all available models
lemonade list
- Hermes Agent
How to use julianmb/DeepSeek-V4-Flash-0731-IQ2XXS-STRIX with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf julianmb/DeepSeek-V4-Flash-0731-IQ2XXS-STRIX
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 julianmb/DeepSeek-V4-Flash-0731-IQ2XXS-STRIX
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use julianmb/DeepSeek-V4-Flash-0731-IQ2XXS-STRIX with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf julianmb/DeepSeek-V4-Flash-0731-IQ2XXS-STRIX
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 "julianmb/DeepSeek-V4-Flash-0731-IQ2XXS-STRIX" \ --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"
DeepSeek-V4-Flash-0731-IQ2XXS-STRIX
Quantized DeepSeek V4 Flash (0731) GGUF for AMD Strix Halo (gfx1151).
Details
- Base model: DeepSeek V4 Flash 0731 (284B MoE)
- Quantization source: tekosML (
DeepSeek-V4-Flash-0731-IQ2XXS-w2Q2K-AProjQ8-SExpQ8-OutQ8-imatrix) - File size: 86.72 GB
- Architecture: 43 routed layers, 256 experts/layer (6 active), 4-stream hyper-connections
Quant Recipe
| Tensor group | Type |
|---|---|
| Attention projections | Q8_0 |
| Shared experts | Q8_0 |
| Output head | Q8_0 |
| Token embedding | F16 |
| Routed gate/up experts | IQ2_XXS |
| Routed down experts | Q2_K |
Recommended Runtime
Run with the julianmb/ds4fa engine on 128 GB Strix Halo:
DS4_ROCM_STREAM_MODEL_CACHE_GB=48 ./ds4 -m DeepSeek-V4-Flash-0731-IQ2XXS-STRIX.gguf -c 512 \
--ssd-streaming --ssd-streaming-cache-experts 32GB \
-p "What is the capital of France?" --think --tokens 60
- Downloads last month
- 191
We're not able to determine the quantization variants.
Model tree for julianmb/DeepSeek-V4-Flash-0731-IQ2XXS-STRIX
Base model
deepseek-ai/DeepSeek-V4-Flash-0731