Instructions to use MedMLX/MLX-Reason-CT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use MedMLX/MLX-Reason-CT 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("MedMLX/MLX-Reason-CT")
config = load_config("MedMLX/MLX-Reason-CT")

# 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 MedMLX/MLX-Reason-CT with Pi:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "MedMLX/MLX-Reason-CT"

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": "MedMLX/MLX-Reason-CT"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent

How to use MedMLX/MLX-Reason-CT 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 "MedMLX/MLX-Reason-CT"

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 MedMLX/MLX-Reason-CT

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use MedMLX/MLX-Reason-CT with OpenClaw:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "MedMLX/MLX-Reason-CT"

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 "MedMLX/MLX-Reason-CT" \
  --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"

josand commited on 3 days ago

Commit

4bf4ef3

verified ·

1 Parent(s): 83d7da6

Install mlx-reason-ct 0.3.6

Browse files

Files changed (1) hide show

README.md +4 -4

README.md CHANGED Viewed

@@ -26,13 +26,13 @@ tags:
 Generate reports and ask questions about 3D chest and abdomen CT, locally on Apple Silicon.
-[GitHub](https://github.com/MedMLX/MLX-Reason-CT) · [Files](https://huggingface.co/MedMLX/MLX-Reason-CT/tree/main) · [Docs](https://github.com/MedMLX/MLX-Reason-CT/blob/main/docs/usage.md)
 | Input | Output |
 | :--- | :--- |
 | 3D CT · NIfTI | Reports and CT question answering |
-**Apple Silicon · Metal · Python 3.13 / 3.14**
 ## Quick start
@@ -40,10 +40,10 @@ Generate reports and ask questions about 3D chest and abdomen CT, locally on App
 uv venv --python 3.13
 source .venv/bin/activate
-uv pip install "mlx-reason-ct==0.3.4"
 uv tool install huggingface-hub
-hf download MedMLX/MLX-Reason-CT --revision bad5a52a1c93178193b174fa78adace150b5f2de --local-dir models
 ```
 Replace the example input paths with your own files.

 Generate reports and ask questions about 3D chest and abdomen CT, locally on Apple Silicon.
+[GitHub](https://github.com/MedMLX/mlx-reason-ct) · [Files](https://huggingface.co/MedMLX/MLX-Reason-CT/tree/main) · [Docs](https://github.com/MedMLX/mlx-reason-ct/blob/v0.3.6/README.md)
 | Input | Output |
 | :--- | :--- |
 | 3D CT · NIfTI | Reports and CT question answering |
+**Apple Silicon · Metal · Python 3.13**
 ## Quick start
 uv venv --python 3.13
 source .venv/bin/activate
+uv pip install "mlx-reason-ct==0.3.6"
 uv tool install huggingface-hub
+hf download MedMLX/MLX-Reason-CT --revision 5e5b5202fd04ac9f63ede203ebc9327aa676ae94 --local-dir models
 ```
 Replace the example input paths with your own files.