Instructions to use jitvimol/typhoon-ocr2-0.8b-mlx-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use jitvimol/typhoon-ocr2-0.8b-mlx-8bit 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("jitvimol/typhoon-ocr2-0.8b-mlx-8bit")
config = load_config("jitvimol/typhoon-ocr2-0.8b-mlx-8bit")

# 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 jitvimol/typhoon-ocr2-0.8b-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 "jitvimol/typhoon-ocr2-0.8b-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": "jitvimol/typhoon-ocr2-0.8b-mlx-8bit"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent

How to use jitvimol/typhoon-ocr2-0.8b-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 "jitvimol/typhoon-ocr2-0.8b-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 jitvimol/typhoon-ocr2-0.8b-mlx-8bit

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use jitvimol/typhoon-ocr2-0.8b-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 "jitvimol/typhoon-ocr2-0.8b-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 "jitvimol/typhoon-ocr2-0.8b-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"

jitvimol commited on 7 days ago

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Add LM Studio usage section

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@@ -40,6 +40,16 @@ The conversion was performed without any additional training or modification of
 This model is in the standard MLX format and can be loaded by any MLX-compatible tool that supports Qwen3.5 vision-language models. Whichever tool is used, apply the prompt given below and set the temperature to 0.
 ### mlx-vlm (command line)
 ```bash

 This model is in the standard MLX format and can be loaded by any MLX-compatible tool that supports Qwen3.5 vision-language models. Whichever tool is used, apply the prompt given below and set the temperature to 0.
+### LM Studio
+In the LM Studio app, search for `jitvimol/typhoon-ocr2-0.8b-mlx-8bit` in the model search, or paste the repository URL, and download it. Alternatively, use the command line:
+```bash
+lms get https://huggingface.co/jitvimol/typhoon-ocr2-0.8b-mlx-8bit
+```
+Then load the model, attach a page image in the chat, and use the prompt given below with the temperature set to 0. If large pages are downscaled in your setup, the layout boxes may differ from the reference results (see Limitations).
 ### mlx-vlm (command line)
 ```bash