Text Generation
Transformers
Safetensors
GGUF
swarm_moe
causal-lm
mixture-of-experts
swarm
agentic-runtime
smolagents
trust-remote-code
bf16
qwen-tokenizer
ollama-compatible-bridge
gguf-preview
full-runtime
conversational
custom_code
Instructions to use ayjays132/PhillSwarm-4b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ayjays132/PhillSwarm-4b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="ayjays132/PhillSwarm-4b", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("ayjays132/PhillSwarm-4b", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use ayjays132/PhillSwarm-4b 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 ayjays132/PhillSwarm-4b:F16 # Run inference directly in the terminal: llama cli -hf ayjays132/PhillSwarm-4b:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf ayjays132/PhillSwarm-4b:F16 # Run inference directly in the terminal: llama cli -hf ayjays132/PhillSwarm-4b:F16
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 ayjays132/PhillSwarm-4b:F16 # Run inference directly in the terminal: ./build/bin/llama cli -hf ayjays132/PhillSwarm-4b:F16
Use Docker
docker model run hf.co/ayjays132/PhillSwarm-4b:F16
- Llama new
- LM Studio
- Jan
- vLLM
How to use ayjays132/PhillSwarm-4b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ayjays132/PhillSwarm-4b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ayjays132/PhillSwarm-4b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/ayjays132/PhillSwarm-4b:F16
- SGLang
How to use ayjays132/PhillSwarm-4b with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "ayjays132/PhillSwarm-4b" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ayjays132/PhillSwarm-4b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "ayjays132/PhillSwarm-4b" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ayjays132/PhillSwarm-4b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Ollama
How to use ayjays132/PhillSwarm-4b with Ollama:
ollama run hf.co/ayjays132/PhillSwarm-4b:F16
- Unsloth Desktop
- Pi
How to use ayjays132/PhillSwarm-4b with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf ayjays132/PhillSwarm-4b:F16
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": "ayjays132/PhillSwarm-4b:F16" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use ayjays132/PhillSwarm-4b with Docker Model Runner:
docker model run hf.co/ayjays132/PhillSwarm-4b:F16
- Lemonade
How to use ayjays132/PhillSwarm-4b with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull ayjays132/PhillSwarm-4b:F16
Run and chat with the model
lemonade run user.PhillSwarm-4b-F16
List all available models
lemonade list
- Hermes Agent
How to use ayjays132/PhillSwarm-4b with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf ayjays132/PhillSwarm-4b:F16
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 ayjays132/PhillSwarm-4b:F16
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use ayjays132/PhillSwarm-4b with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf ayjays132/PhillSwarm-4b:F16
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 "ayjays132/PhillSwarm-4b:F16" \ --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 swarm_app_config.example.json from ayjays132/PhillSwarm-4b: direct link, hf CLI and curl.
- Browser
- Download file 1.38 kB
-
https://huggingface.co/ayjays132/PhillSwarm-4b/resolve/main/swarm_app_config.example.json
- Command line
-
hf download hf://ayjays132/PhillSwarm-4b/swarm_app_config.example.json
-
curl -L -o swarm_app_config.example.json https://huggingface.co/ayjays132/PhillSwarm-4b/resolve/main/swarm_app_config.example.json
1.38 kB
| { | |
| "model_path": ".", | |
| "swarm_config": "swarm_runtime_config.json", | |
| "host": "127.0.0.1", | |
| "port": 7860, | |
| "device": "auto", | |
| "dtype": "bfloat16", | |
| "permission_mode": "default", | |
| "auto_open": true, | |
| "enable_model_chat": true, | |
| "enable_tools": true, | |
| "enable_browser_tools": true, | |
| "enable_website_builder": true, | |
| "route_judge_enabled": true, | |
| "force_profile_debate": false, | |
| "streaming_enabled": true, | |
| "stream_token_chunks": true, | |
| "execute_tool_calls": true, | |
| "auto_web_search": true, | |
| "auto_web_search_policy": "factual_or_research", | |
| "auto_web_search_max_results": 5, | |
| "default_persona": "phill_core", | |
| "default_depth": "balanced", | |
| "publish_safe": true, | |
| "state_dir": "state", | |
| "browser_headless": false, | |
| "browser_timeout_ms": 30000, | |
| "browser_capture_dir": "state/browser_captures", | |
| "browser_ocr": true, | |
| "enable_mcp_bridge": true, | |
| "mcp_allow_lan": false, | |
| "mcp_auth_token": "", | |
| "mcp_endpoint_path": "/mcp", | |
| "mcp_public_base_url": "", | |
| "mcp_external_servers": [], | |
| "max_route_tools": 8, | |
| "metadata": { | |
| "description": "Local ChatGPT-style Phill Swarm app with goals, scaffold routing, DDGS/web search, Playwright/browser tools, and website drafting.", | |
| "setup_command": "python launch_swarm_app.py --install", | |
| "headless_command": "python launch_swarm_app.py --install --headless", | |
| "visible_browser_default": true | |
| } | |
| } | |