Instructions to use EZCon/GLM-OCR-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use EZCon/GLM-OCR-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-mlx") config = load_config("EZCon/GLM-OCR-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
- Pi
How to use EZCon/GLM-OCR-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-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-mlx" } ] } } }Run Pi
# Start Pi in your project directory: pi
- OpenClaw new
How to use EZCon/GLM-OCR-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-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-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"
- Hermes Agent
How to use EZCon/GLM-OCR-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-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-mlx
Run Hermes
hermes
| [gMASK]<sop> | |
| {%- if tools -%} | |
| <|system|> | |
| # Tools | |
| You may call one or more functions to assist with the user query. | |
| You are provided with function signatures within <tools></tools> XML tags: | |
| <tools> | |
| {% for tool in tools %} | |
| {{ tool | tojson(ensure_ascii=False) }} | |
| {% endfor %} | |
| </tools> | |
| For each function call, output the function name and arguments within the following XML format: | |
| <tool_call>{function-name} | |
| <arg_key>{arg-key-1}</arg_key> | |
| <arg_value>{arg-value-1}</arg_value> | |
| <arg_key>{arg-key-2}</arg_key> | |
| <arg_value>{arg-value-2}</arg_value> | |
| ... | |
| </tool_call>{%- endif -%} | |
| {%- macro visible_text(content) -%} | |
| {%- if content is string -%} | |
| {{- content }} | |
| {%- elif content is iterable and content is not mapping -%} | |
| {%- for item in content -%} | |
| {%- if item is mapping and item.type == 'text' -%} | |
| {{- item.text }} | |
| {%- elif item is mapping and (item.type == 'image' or 'image' in item) -%} | |
| <|begin_of_image|><|image|><|end_of_image|> | |
| {%- elif item is mapping and (item.type == 'video' or 'video' in item) -%} | |
| <|begin_of_video|><|video|><|end_of_video|> | |
| {%- elif item is string -%} | |
| {{- item }} | |
| {%- endif -%} | |
| {%- endfor -%} | |
| {%- else -%} | |
| {{- content }} | |
| {%- endif -%} | |
| {%- endmacro -%} | |
| {%- set ns = namespace(last_user_index=-1) %} | |
| {%- for m in messages %} | |
| {%- if m.role == 'user' %} | |
| {% set ns.last_user_index = loop.index0 -%} | |
| {%- endif %} | |
| {%- endfor %} | |
| {% for m in messages %} | |
| {%- if m.role == 'user' -%}<|user|> | |
| {% if m.content is string %} | |
| {{ m.content }} | |
| {%- else %} | |
| {%- for item in m.content %} | |
| {% if item.type == 'video' or 'video' in item %} | |
| <|begin_of_video|><|video|><|end_of_video|>{% elif item.type == 'image' or 'image' in item %} | |
| <|begin_of_image|><|image|><|end_of_image|>{% elif item.type == 'text' %} | |
| {{ item.text }} | |
| {%- endif %} | |
| {%- endfor %} | |
| {%- endif %} | |
| {{- '/nothink' if (enable_thinking is defined and not enable_thinking and not visible_text(m.content).endswith("/nothink")) else '' -}} | |
| {%- elif m.role == 'assistant' -%} | |
| <|assistant|> | |
| {%- set reasoning_content = '' %} | |
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| {%- if m.reasoning_content is string %} | |
| {%- set reasoning_content = m.reasoning_content %} | |
| {%- else %} | |
| {%- if '</think>' in content %} | |
| {%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %} | |
| {%- set content = content.split('</think>')[-1].lstrip('\n') %} | |
| {%- endif %} | |
| {%- endif %} | |
| {%- if loop.index0 > ns.last_user_index and reasoning_content -%} | |
| {{ '\n<think>' + reasoning_content.strip() + '</think>'}} | |
| {%- else -%} | |
| {{ '\n<think></think>' }} | |
| {%- endif -%} | |
| {%- if content.strip() -%} | |
| {{ '\n' + content.strip() }} | |
| {%- endif -%} | |
| {% if m.tool_calls %} | |
| {% for tc in m.tool_calls %} | |
| {%- if tc.function %} | |
| {%- set tc = tc.function %} | |
| {%- endif %} | |
| {{ '\n<tool_call>' + tc.name }} | |
| {% set _args = tc.arguments %} | |
| {% for k, v in _args.items() %} | |
| <arg_key>{{ k }}</arg_key> | |
| <arg_value>{{ v | tojson(ensure_ascii=False) if v is not string else v }}</arg_value> | |
| {% endfor %} | |
| </tool_call>{% endfor %} | |
| {% endif %} | |
| {%- elif m.role == 'tool' -%} | |
| {%- if m.content is string -%} | |
| {%- if loop.first or (messages[loop.index0 - 1].role != "tool") %} | |
| {{- '<|observation|>' }} | |
| {%- endif %} | |
| {{- '\n<tool_response>\n' }} | |
| {{- m.content }} | |
| {{- '\n</tool_response>' }} | |
| {% elif m.content is iterable and m.content is not mapping %} | |
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| {{- '<|observation|>' }} | |
| {%- endif %} | |
| {{- '\n<tool_response>\n' }} | |
| {%- for tr in m.content -%} | |
| {%- if tr is mapping and tr.type is defined -%} | |
| {%- set t = tr.type | lower -%} | |
| {%- if t == 'text' and tr.text is defined -%} | |
| {{ tr.text }} | |
| {%- elif t in ['image', 'image_url'] -%} | |
| <|begin_of_image|><|image|><|end_of_image|> | |
| {%- elif t in ['video', 'video_url'] -%} | |
| <|begin_of_video|><|video|><|end_of_video|> | |
| {%- else -%} | |
| {{ tr | tojson(ensure_ascii=False) }} | |
| {%- endif -%} | |
| {%- else -%} | |
| {{ tr.output if tr.output is defined else tr }} | |
| {%- endif -%} | |
| {%- endfor -%} | |
| {{- '\n</tool_response>' }} | |
| {%- else -%} | |
| <|observation|>{% for tr in m.content %} | |
| <tool_response> | |
| {{ tr.output if tr.output is defined else tr }} | |
| </tool_response>{% endfor -%} | |
| {% endif -%} | |
| {%- elif m.role == 'system' -%} | |
| <|system|> | |
| {{ visible_text(m.content) }} | |
| {%- endif -%} | |
| {%- endfor -%} | |
| {%- if add_generation_prompt -%} | |
| <|assistant|> | |
| {{'<think></think>\n' if (enable_thinking is defined and not enable_thinking) else ''}} | |
| {%- endif -%} | |