Instructions to use LaplAI/gua with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

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

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

File size: 1,410 Bytes

{
  "dev": "experiments/decision/dev-v3-lora-v3.jsonl",
  "eval": "experiments/decision/eval-v3-lora-v3.jsonl",
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      },
      "eval_log_loss": {
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        "after": 1.0632
      }
    },
    "action": {
      "temperature": 2.15,
      "dev_items": 4006,
      "dev_ece": {
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      "dev_log_loss": {
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        "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": {
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        "after": 0.1405
      },
      "eval_log_loss": {
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      }
    }
  }
}