Instructions to use Accio-Lab/occamy-1.0-MLX-8bit 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-8bit 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-8bit") 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-8bit 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-8bit"
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-8bit" } ] } } }Run Pi
# Start Pi in your project directory: pi
- MLX LM
How to use Accio-Lab/occamy-1.0-MLX-8bit 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-8bit"
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-8bit" # 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-8bit", "messages": [ {"role": "user", "content": "Hello"} ] }' - Hermes Agent
How to use Accio-Lab/occamy-1.0-MLX-8bit 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-8bit"
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-8bit
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use Accio-Lab/occamy-1.0-MLX-8bit 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-8bit"
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-8bit" \ --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 api_validation.json from Accio-Lab/occamy-1.0-MLX-8bit: direct link, hf CLI and curl.
- Browser
- Download file 2.57 kB
-
https://huggingface.co/Accio-Lab/occamy-1.0-MLX-8bit/resolve/main/api_validation.json
- Command line
-
hf download hf://Accio-Lab/occamy-1.0-MLX-8bit/api_validation.json
-
curl -L -o api_validation.json https://huggingface.co/Accio-Lab/occamy-1.0-MLX-8bit/resolve/main/api_validation.json
2.57 kB
| { | |
| "bits": 8, | |
| "backend": "Linux MLX CUDA 12 on NVIDIA B200", | |
| "runtime": "stock mlx_lm.server 0.31.3", | |
| "thinking": false, | |
| "temperature": 0, | |
| "endpoint": "/v1/chat/completions", | |
| "scope": "Two authored HTTP smoke checks; Mac Metal pending. No agent or tool-call compatibility claim.", | |
| "checks": [ | |
| { | |
| "id": "arithmetic", | |
| "request": { | |
| "model": "default_model", | |
| "messages": [ | |
| { | |
| "role": "user", | |
| "content": "Compute 2+2. Answer briefly." | |
| } | |
| ], | |
| "temperature": 0, | |
| "max_tokens": 128, | |
| "stream": false | |
| }, | |
| "response": { | |
| "id": "chatcmpl-ed4928d9-5c3b-436c-a4c2-111ac3b0632d", | |
| "system_fingerprint": "0.31.3-0.32.2-Linux-5.10.134-19.1.al8.x86_64-x86_64-with-glibc2.39-sm_100", | |
| "object": "chat.completion", | |
| "model": "default_model", | |
| "created": 1790974928, | |
| "choices": [ | |
| { | |
| "index": 0, | |
| "finish_reason": "stop", | |
| "message": { | |
| "role": "assistant", | |
| "content": "4" | |
| } | |
| } | |
| ], | |
| "usage": { | |
| "prompt_tokens": 21, | |
| "completion_tokens": 2, | |
| "total_tokens": 23, | |
| "prompt_tokens_details": { | |
| "cached_tokens": 0 | |
| } | |
| } | |
| }, | |
| "passed": true | |
| }, | |
| { | |
| "id": "json", | |
| "request": { | |
| "model": "default_model", | |
| "messages": [ | |
| { | |
| "role": "user", | |
| "content": "Return only valid JSON with no markdown. The object must be exactly {\"city\":\"Paris\",\"count\":3}." | |
| } | |
| ], | |
| "temperature": 0, | |
| "max_tokens": 128, | |
| "stream": false | |
| }, | |
| "response": { | |
| "id": "chatcmpl-bfe70a66-61b3-471a-ab86-f16196b0c452", | |
| "system_fingerprint": "0.31.3-0.32.2-Linux-5.10.134-19.1.al8.x86_64-x86_64-with-glibc2.39-sm_100", | |
| "object": "chat.completion", | |
| "model": "default_model", | |
| "created": 1790974977, | |
| "choices": [ | |
| { | |
| "index": 0, | |
| "finish_reason": "stop", | |
| "message": { | |
| "role": "assistant", | |
| "content": "{\"city\":\"Paris\",\"count\":3}" | |
| } | |
| } | |
| ], | |
| "usage": { | |
| "prompt_tokens": 34, | |
| "completion_tokens": 10, | |
| "total_tokens": 44, | |
| "prompt_tokens_details": { | |
| "cached_tokens": 0 | |
| } | |
| } | |
| }, | |
| "passed": true | |
| } | |
| ], | |
| "owned_server_stopped": true | |
| } |