Fox Models (text)
Collection
11 items • Updated • 1
How to use teolm30/fox1.2 with llama.cpp:
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf teolm30/fox1.2 # Run inference directly in the terminal: llama cli -hf teolm30/fox1.2
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf teolm30/fox1.2 # Run inference directly in the terminal: llama cli -hf teolm30/fox1.2
# 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 teolm30/fox1.2 # Run inference directly in the terminal: ./llama-cli -hf teolm30/fox1.2
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 teolm30/fox1.2 # Run inference directly in the terminal: ./build/bin/llama-cli -hf teolm30/fox1.2
docker model run hf.co/teolm30/fox1.2
How to use teolm30/fox1.2 with Ollama:
ollama run hf.co/teolm30/fox1.2
How to use teolm30/fox1.2 with Unsloth Studio:
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 teolm30/fox1.2 to start chatting
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 teolm30/fox1.2 to start chatting
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for teolm30/fox1.2 to start chatting
How to use teolm30/fox1.2 with Docker Model Runner:
docker model run hf.co/teolm30/fox1.2
How to use teolm30/fox1.2 with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull teolm30/fox1.2
lemonade run user.fox1.2-{{QUANT_TAG}}lemonade list
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf teolm30/fox1.2# Run inference directly in the terminal:
llama cli -hf teolm30/fox1.2# 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 teolm30/fox1.2# Run inference directly in the terminal:
./llama-cli -hf teolm30/fox1.2git 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 teolm30/fox1.2# Run inference directly in the terminal:
./build/bin/llama-cli -hf teolm30/fox1.2docker model run hf.co/teolm30/fox1.2YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
A fine-tuned Qwen2.5-0.5B model optimized for OpenClaw agent tool execution.
When you need to execute a tool, respond with JSON in this format:
{"action": "tool_name", "param1": "value1", "param2": "value2"}
{"action": "exec", "command": "ls -la"}
{"action": "read", "path": "/home/user/README.md"}
{"action": "write", "path": "/home/user/test.txt", "content": "Hello World"}
{"action": "web_search", "query": "python tutorials"}
{"action": "weather", "location": "Athens"}
{"action": "cron", "action": "list"}
{"action": "session_status"}
# Create the model
ollama create fox1.2-openclaw -f Modelfile
# Run it
ollama run fox1.2-openclaw "list files in current directory"
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained("teolm30/fox1.2-openclaw")
tokenizer = AutoTokenizer.from_pretrained("teolm30/fox1.2-openclaw")
# Generate tool call
inputs = tokenizer("List all files", return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=256)
print(tokenizer.decode(outputs[0]))
# Download
huggingface-cli download teolm30/fox1.2-openclaw
# Or use curl
curl -L -o fox1.2-openclaw.gguf https://huggingface.co/teolm30/fox1.2-opencloak/resolve/main/fox1.2-openclaw.gguf
Trained on 200+ examples covering all OpenClaw tool patterns:
Optimized for tool call generation and execution in agent workflows.
Add to your models.json:
{
"id": "fox1.2-openclaw:latest",
"name": "Fox1.2 OpenClaw",
"reasoning": false,
"input": ["text"],
"contextWindow": 32768,
"maxTokens": 4096,
"api": "ollama"
}
Then restart OpenClaw: openclaw gateway restart
Apache 2.0
teolm30 (OpenClaw Community)
ollama run hf.co/teolm30/fox1.2
Install (macOS, Linux)
# Start a local OpenAI-compatible server with a web UI: llama serve -hf teolm30/fox1.2# Run inference directly in the terminal: llama cli -hf teolm30/fox1.2