Instructions to use Accio-Lab/occamy-1.0-MLX-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use Accio-Lab/occamy-1.0-MLX-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("Accio-Lab/occamy-1.0-MLX-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 Settings
- LM Studio
- Pi
How to use Accio-Lab/occamy-1.0-MLX-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 "Accio-Lab/occamy-1.0-MLX-4bit"
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "mlx-lm": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "Accio-Lab/occamy-1.0-MLX-4bit" } ] } } }Run Pi
# Start Pi in your project directory: pi
- MLX LM
How to use Accio-Lab/occamy-1.0-MLX-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 "Accio-Lab/occamy-1.0-MLX-4bit"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "Accio-Lab/occamy-1.0-MLX-4bit" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Accio-Lab/occamy-1.0-MLX-4bit", "messages": [ {"role": "user", "content": "Hello"} ] }' - Hermes Agent
How to use Accio-Lab/occamy-1.0-MLX-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 "Accio-Lab/occamy-1.0-MLX-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 Accio-Lab/occamy-1.0-MLX-4bit
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use Accio-Lab/occamy-1.0-MLX-4bit with OpenClaw:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "Accio-Lab/occamy-1.0-MLX-4bit"
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 "Accio-Lab/occamy-1.0-MLX-4bit" \ --custom-provider-id mlx-lm \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
Download validation_summary.json from Accio-Lab/occamy-1.0-MLX-4bit: direct link, hf CLI and curl.
- Browser
- Download file 2.55 kB
-
https://huggingface.co/Accio-Lab/occamy-1.0-MLX-4bit/resolve/main/validation_summary.json
- Command line
-
hf download hf://Accio-Lab/occamy-1.0-MLX-4bit/validation_summary.json
-
curl -L -o validation_summary.json https://huggingface.co/Accio-Lab/occamy-1.0-MLX-4bit/resolve/main/validation_summary.json
2.55 kB
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| "passed": true, | |
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| "group_size": 64, | |
| "mac_metal_acceptance": "pending", | |
| "linux_native_reload_passed": true, | |
| "all_dequantized_rows_finite": true, | |
| "generation": { | |
| "status": "passed", | |
| "scope": "Linux native MLX CPU cached greedy, one short text prompt; no Mac Metal or quality claim", | |
| "passed": true, | |
| "prompt": "<|im_start|>user\nCompute 2+2. Answer briefly.<|im_end|>\n<|im_start|>assistant\n<think>\n\n</think>\n\n", | |
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| "text": "4<|im_end|>", | |
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