Instructions to use LaplAI/gua with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use LaplAI/gua with MLX:
# Make sure mlx-vlm is installed # pip install --upgrade mlx-vlm from mlx_vlm import load, generate from mlx_vlm.prompt_utils import apply_chat_template from mlx_vlm.utils import load_config # Load the model model, processor = load("LaplAI/gua") config = load_config("LaplAI/gua") # Prepare input image = ["http://images.cocodataset.org/val2017/000000039769.jpg"] prompt = "Describe this image." # Apply chat template formatted_prompt = apply_chat_template( processor, config, prompt, num_images=1 ) # Generate output output = generate(model, processor, formatted_prompt, image) print(output) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Pi
How to use LaplAI/gua with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "LaplAI/gua"
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": "LaplAI/gua" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent
How to use LaplAI/gua 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 "LaplAI/gua"
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 LaplAI/gua
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use LaplAI/gua with OpenClaw:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "LaplAI/gua"
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 "LaplAI/gua" \ --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"
gua v2: continue v1 on 12,000 balanced questions from macos-cua v3 (adds Logic Pro, OBS, Plasticity)
1357427 verified Download temperatures.json from LaplAI/gua: direct link, hf CLI and curl.
- Browser
- Download file 1.41 kB
-
https://huggingface.co/LaplAI/gua/resolve/main/temperatures.json
- Command line
-
hf download hf://LaplAI/gua/temperatures.json
-
curl -L -o temperatures.json https://huggingface.co/LaplAI/gua/resolve/main/temperatures.json
1.41 kB
| { | |
| "dev": "experiments/decision/dev-v3-lora-v3.jsonl", | |
| "eval": "experiments/decision/eval-v3-lora-v3.jsonl", | |
| "questions": { | |
| "grounding": { | |
| "temperature": 1.25, | |
| "dev_items": 2555, | |
| "dev_ece": { | |
| "before": 0.2877, | |
| "after": 0.2073 | |
| }, | |
| "dev_log_loss": { | |
| "before": 1.0868, | |
| "after": 1.0408 | |
| }, | |
| "eval_items": 6508, | |
| "eval_ece": { | |
| "before": 0.259, | |
| "after": 0.1725 | |
| }, | |
| "eval_log_loss": { | |
| "before": 1.1036, | |
| "after": 1.0632 | |
| } | |
| }, | |
| "action": { | |
| "temperature": 2.15, | |
| "dev_items": 4006, | |
| "dev_ece": { | |
| "before": 0.3158, | |
| "after": 0.0655 | |
| }, | |
| "dev_log_loss": { | |
| "before": 1.9669, | |
| "after": 1.4436 | |
| }, | |
| "eval_items": 9972, | |
| "eval_ece": { | |
| "before": 0.2941, | |
| "after": 0.0603 | |
| }, | |
| "eval_log_loss": { | |
| "before": 1.9069, | |
| "after": 1.4122 | |
| } | |
| }, | |
| "next_target": { | |
| "temperature": 1.2, | |
| "dev_items": 2555, | |
| "dev_ece": { | |
| "before": 0.2854, | |
| "after": 0.1744 | |
| }, | |
| "dev_log_loss": { | |
| "before": 2.5119, | |
| "after": 2.4338 | |
| }, | |
| "eval_items": 6508, | |
| "eval_ece": { | |
| "before": 0.2527, | |
| "after": 0.1405 | |
| }, | |
| "eval_log_loss": { | |
| "before": 2.5645, | |
| "after": 2.483 | |
| } | |
| } | |
| } | |
| } |