Image-Text-to-Text
GGUF
qwen4_exp
mixed-quant
qwen4exp
qwen3.8-flash-next
swift1.5
ds4
dgx-spark
ssd-offload
conversational
Instructions to use Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-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 Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-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 Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF:BF16 # Run inference directly in the terminal: llama cli -hf Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF:BF16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF:BF16 # Run inference directly in the terminal: llama cli -hf Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF:BF16
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 Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF:BF16 # Run inference directly in the terminal: ./llama-cli -hf Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF:BF16
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 Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF:BF16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF:BF16
Use Docker
docker model run hf.co/Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF:BF16
- LM Studio
- Jan
- vLLM
How to use Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-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": "Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker
docker model run hf.co/Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF:BF16
- Ollama
How to use Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF with Ollama:
ollama run hf.co/Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF:BF16
- Unsloth Desktop
- Pi
How to use Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-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": "Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF:BF16" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF with Docker Model Runner:
docker model run hf.co/Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF:BF16
- Lemonade
How to use Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF:BF16
Run and chat with the model
lemonade run user.Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF-BF16
List all available models
lemonade list
- Hermes Agent
How to use Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-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 Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-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 Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF:BF16
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-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 "Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-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"
Download SHA256SUMS from Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF: direct link, hf CLI and curl.
- Browser
- Download file 1.06 kB
-
https://huggingface.co/Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF/resolve/main/SHA256SUMS
- Command line
-
hf download hf://Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF/SHA256SUMS
-
curl -L -o SHA256SUMS https://huggingface.co/Baekpica/Swift1.5-Qwen3.8-Flash-Next-Mixed-Quant-GGUF/resolve/main/SHA256SUMS
1.06 kB
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