Instructions to use EZCon/GLM-OCR-8bit-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use EZCon/GLM-OCR-8bit-mlx 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("EZCon/GLM-OCR-8bit-mlx")
config = load_config("EZCon/GLM-OCR-8bit-mlx")

# 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 EZCon/GLM-OCR-8bit-mlx with Pi:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "EZCon/GLM-OCR-8bit-mlx"

Configure the model in Pi

# Install Pi:
npm install -g @mariozechner/pi-coding-agent
# Add to ~/.pi/agent/models.json:
{
  "providers": {
    "mlx-lm": {
      "baseUrl": "http://localhost:8080/v1",
      "api": "openai-completions",
      "apiKey": "none",
      "models": [
        {
          "id": "EZCon/GLM-OCR-8bit-mlx"
        }
      ]
    }
  }
}

Run Pi

# Start Pi in your project directory:
pi

Hermes Agent

How to use EZCon/GLM-OCR-8bit-mlx 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 "EZCon/GLM-OCR-8bit-mlx"

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 EZCon/GLM-OCR-8bit-mlx

Run Hermes

hermes

Atomic Chat

OpenClaw

How to use EZCon/GLM-OCR-8bit-mlx with OpenClaw:

Start the MLX server

# Install MLX LM:
uv tool install mlx-lm
# Start a local OpenAI-compatible server:
mlx_lm.server --model "EZCon/GLM-OCR-8bit-mlx"

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 "EZCon/GLM-OCR-8bit-mlx" \
  --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"

hermeschen-ezcon commited on May 30

Commit

7829948

verified ·

1 Parent(s): 14e7189

Upload folder using huggingface_hub

Browse files

Files changed (3) hide show

README.md +1 -1
model.safetensors +2 -2
processor_config.json +5 -7

README.md CHANGED Viewed

@@ -11,9 +11,9 @@ language:
 - ko
 library_name: mlx
 base_model: zai-org/GLM-OCR
-pipeline_tag: image-text-to-text
 tags:
 - mlx
 ---
 # EZCon/GLM-OCR-8bit-mlx

 - ko
 library_name: mlx
 base_model: zai-org/GLM-OCR
 tags:
 - mlx
+pipeline_tag: image-text-to-text
 ---
 # EZCon/GLM-OCR-8bit-mlx

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processor_config.json CHANGED Viewed

@@ -1,9 +1,9 @@
 {
   "image_processor": {
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     "do_rescale": true,
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-    "temporal_patch_size": 2
   },
   "processor_class": "GlmOcrProcessor"
 }

 {
   "image_processor": {
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     "do_convert_rgb": true,
     "do_normalize": true,
     "do_rescale": true,
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     "rescale_factor": 0.00392156862745098,
+    "temporal_patch_size": 2,
+    "use_transformers_backend": true
   },
   "processor_class": "GlmOcrProcessor"
 }