Instructions to use mlx-community/DiffuCoder-7B-cpGRPO-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/DiffuCoder-7B-cpGRPO-4bit with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("mlx-community/DiffuCoder-7B-cpGRPO-4bit") prompt = "Write a story about Einstein" messages = [{"role": "user", "content": prompt}] prompt = tokenizer.apply_chat_template( messages, add_generation_prompt=True ) text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
- Pi new
How to use mlx-community/DiffuCoder-7B-cpGRPO-4bit with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "mlx-community/DiffuCoder-7B-cpGRPO-4bit"
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "mlx-lm": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "mlx-community/DiffuCoder-7B-cpGRPO-4bit" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use mlx-community/DiffuCoder-7B-cpGRPO-4bit with Hermes Agent:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "mlx-community/DiffuCoder-7B-cpGRPO-4bit"
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 mlx-community/DiffuCoder-7B-cpGRPO-4bit
Run Hermes
hermes
- MLX LM
How to use mlx-community/DiffuCoder-7B-cpGRPO-4bit with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "mlx-community/DiffuCoder-7B-cpGRPO-4bit"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "mlx-community/DiffuCoder-7B-cpGRPO-4bit" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "mlx-community/DiffuCoder-7B-cpGRPO-4bit", "messages": [ {"role": "user", "content": "Hello"} ] }'
🥲 Failed to load the model
Using LMStudio on M1 Mac Mini:
🥲 Failed to load the model
Failed to load model
Error when loading model: ValueError: Model type Dream not supported.
You have to wait for the new MLX-LM update and that LM Studio adapts it into the new version too.
Thanks mate. Am currently running 0.3.17.
Hi I`ve tried to use https://github.com/ml-explore/mlx-lm/pull/270 and had an error with shape:
970 # Prepare max length
--> 971 input_length = prompt.shape[1]
972 if generation_config.max_new_tokens is not None:
973 generation_config.max_length = generation_config.max_new_tokens + input_length
- when i fix the hape to [1] the responce was empty.
@sdfgtr455yytrers thanks for trying my PR, ill continue optmimizing the inference, its currently really slow. you would have to use the "python -m generate_diffusion" command and eddit the prompt inside the file too, once i get this running nice, ill add it into generate itself.