--- language: - en license: other library_name: transformers tags: - tool-calling - mcp - browser-automation - lora - ccmcp - mlx base_model: Qwen/Qwen2.5-Coder-3B-Instruct datasets: - custom pipeline_tag: text-generation --- # qwen-3b-ccmcp-v1 Qwen 3B trained for Claude Chrome MCP tool calling > **Attribution:** Built with Qwen ## Model Description Fine-tuned for MCP (Model Context Protocol) tool calling with the Claude Chrome extension. The model generates tool calls for browser automation tasks. ## Training Details - **Base Model:** Qwen/Qwen2.5-Coder-3B-Instruct - **Method:** LoRA fine-tuning on Apple Silicon (MLX) - **Dataset:** 1,782 MCP browser automation examples - **Validation Loss:** 0.077 - **Iterations:** 1000 - **Naming Convention:** `{base}-{size}-ccmcp-{version}` - `ccmcp` = **C**laude **C**hrome **MCP** ## Files - `adapters.safetensors` - LoRA adapter weights - `adapter_config.json` - LoRA configuration - `qwen-3b-ccmcp-v1-f16.gguf` - GGUF F16 format for llama.cpp/Ollama - `checkpoints/` - Training checkpoints ## Usage ### With MLX (Apple Silicon) ```python from mlx_lm import load, generate from mlx_lm.sample_utils import make_sampler model, tokenizer = load( "mlx-community/Qwen2.5-Coder-3B-Instruct-4bit", adapter_path="pierretokns/qwen-3b-ccmcp-v1" ) messages = [ {"role": "system", "content": "You are a browser automation assistant with MCP tools."}, {"role": "user", "content": "Go to google.com"} ] prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True) sampler = make_sampler(temp=0.1) response = generate(model, tokenizer, prompt=prompt, max_tokens=150, sampler=sampler) print(response) ``` ### With Ollama ```bash # Download GGUF from this repo # Create Modelfile: cat > Modelfile << 'EOF' FROM ./qwen-3b-ccmcp-v1-f16.gguf PARAMETER num_ctx 8192 PARAMETER temperature 0.1 SYSTEM "You are a browser automation assistant with MCP tools." EOF # Create and run ollama create qwen-3b-ccmcp-v1 -f Modelfile ollama run qwen-3b-ccmcp-v1 "Go to google.com" ``` ### With Claude Code + Ollama ```bash ANTHROPIC_BASE_URL=http://localhost:11434 \ ANTHROPIC_AUTH_TOKEN=ollama \ ANTHROPIC_API_KEY=ollama \ claude --model qwen-3b-ccmcp-v1 ``` ## MCP Tools The model was trained on 16 MCP browser automation tools: navigate, read_page, find, computer, form_input, get_page_text, screenshot, javascript_tool, tabs_context_mcp, tabs_create_mcp, gif_creator, upload_image, read_console_messages, read_network_requests, shortcuts_list, shortcuts_execute ## License This model inherits the license from the base model. See [Qwen/Qwen2.5-Coder-3B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-3B-Instruct) for license details. Full license: [https://huggingface.co/Qwen/Qwen2.5-Coder-3B-Instruct/blob/main/LICENSE](https://huggingface.co/Qwen/Qwen2.5-Coder-3B-Instruct/blob/main/LICENSE)