Instructions to use zai-org/GLM-OCR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zai-org/GLM-OCR with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "image-to-text" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("image-to-text", model="zai-org/GLM-OCR") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] pipe(text=messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("zai-org/GLM-OCR") model = AutoModelForMultimodalLM.from_pretrained("zai-org/GLM-OCR", device_map="auto") messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=256) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- AMD Developer Cloud
IvanWong
#62
by lkwlvan - opened
- README.md +99 -8
- config.json +26 -33
- processor_config.json +0 -63
- tokenizer_config.json +3 -4
README.md
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pipeline_tag: image-to-text
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library_name: transformers
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tags:
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- conversational
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---
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# GLM-OCR
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Note that the SDK is currently designed for document parsing tasks only. For information extraction tasks, please refer to the following section and run inference directly with the model.
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###
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### Prompt Limited
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library_name: transformers
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---
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# GLM-OCR
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Note that the SDK is currently designed for document parsing tasks only. For information extraction tasks, please refer to the following section and run inference directly with the model.
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### vLLM
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1. run
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```bash
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pip install -U vllm --extra-index-url https://wheels.vllm.ai/nightly
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```
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or using docker with:
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```
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docker pull vllm/vllm-openai:nightly
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```
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2. run with:
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```bash
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pip install git+https://github.com/huggingface/transformers.git
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vllm serve zai-org/GLM-OCR --allowed-local-media-path / --port 8080
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```
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### SGLang
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1. using docker with:
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```bash
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docker pull lmsysorg/sglang:dev
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```
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or build it from source with:
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```bash
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pip install git+https://github.com/sgl-project/sglang.git#subdirectory=python
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```
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2. run with:
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```bash
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pip install git+https://github.com/huggingface/transformers.git
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python -m sglang.launch_server --model zai-org/GLM-OCR --port 8080
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```
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### Ollama
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1. Download [Ollama](https://ollama.com/download).
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2. run with:
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```bash
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ollama run glm-ocr
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```
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Ollama will automatically use image file path when an image is dragged into the terminal:
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```bash
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ollama run glm-ocr Text Recognition: ./image.png
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```
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### Transformers
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```
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pip install git+https://github.com/huggingface/transformers.git
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```
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```python
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from transformers import AutoProcessor, AutoModelForImageTextToText
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import torch
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MODEL_PATH = "zai-org/GLM-OCR"
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messages = [
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{
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"role": "user",
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"content": [
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{
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"type": "image",
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"url": "test_image.png"
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},
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{
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"type": "text",
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"text": "Text Recognition:"
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}
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],
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}
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]
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processor = AutoProcessor.from_pretrained(MODEL_PATH)
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model = AutoModelForImageTextToText.from_pretrained(
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pretrained_model_name_or_path=MODEL_PATH,
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torch_dtype="auto",
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device_map="auto",
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)
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inputs = processor.apply_chat_template(
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messages,
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tokenize=True,
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add_generation_prompt=True,
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return_dict=True,
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return_tensors="pt"
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).to(model.device)
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inputs.pop("token_type_ids", None)
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generated_ids = model.generate(**inputs, max_new_tokens=8192)
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output_text = processor.decode(generated_ids[0][inputs["input_ids"].shape[1]:], skip_special_tokens=False)
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print(output_text)
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```
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### Prompt Limited
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config.json
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"architectures": [
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"GlmOcrForConditionalGeneration"
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],
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"image_end_token_id": 59257,
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"image_start_token_id": 59256,
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"image_token_id": 59280,
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"model_type": "glm_ocr",
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"text_config": {
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"eos_token_id": [
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],
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"head_dim": 128,
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"hidden_act": "silu",
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"hidden_size": 1536,
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"initializer_range": 0.02,
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"intermediate_size": 4608,
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"max_position_embeddings": 131072,
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"model_type": "glm_ocr_text",
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"num_attention_heads": 16,
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"num_hidden_layers": 16,
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"num_key_value_heads": 8,
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"num_nextn_predict_layers": 1,
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"
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"rms_norm_eps": 1e-05,
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"rope_parameters": {
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"mrope_section": [
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16,
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24,
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],
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"rope_type": "default"
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},
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"tie_word_embeddings": false,
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"use_cache": true
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"vocab_size": 59392
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},
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"tie_word_embeddings": false,
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"transformers_version": "5.17.0",
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"video_end_token_id": 59259,
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"video_start_token_id": 59258,
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"video_token_id": 59281,
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"vision_config": {
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"depth": 24,
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"hidden_act": "silu",
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"hidden_dropout_prob": 0.0,
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"hidden_size": 1024,
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"image_size": 336,
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"in_channels": 3,
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"initializer_range": 0.02,
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"
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"model_type": "glm_ocr_vision",
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"num_heads": 16,
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"out_hidden_size": 1536,
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"patch_size": 14,
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"rms_norm_eps": 1e-05,
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"rope_parameters": {
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"rope_theta": 10000.0,
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"rope_type": "axial"
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},
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"spatial_merge_size": 2,
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"temporal_patch_size": 2
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}
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}
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"architectures": [
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"GlmOcrForConditionalGeneration"
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],
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"model_type": "glm_ocr",
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"text_config": {
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"model_type": "glm_ocr_text",
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"pad_token_id": 59246,
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"vocab_size": 59392,
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"eos_token_id": [
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59246,
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"head_dim": 128,
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"hidden_act": "silu",
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"hidden_size": 1536,
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"initializer_range": 0.02,
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"intermediate_size": 4608,
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"max_position_embeddings": 131072,
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"num_attention_heads": 16,
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"num_hidden_layers": 16,
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"num_nextn_predict_layers": 1,
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"num_key_value_heads": 8,
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"rms_norm_eps": 1e-05,
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"dtype": "bfloat16",
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"rope_parameters": {
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"rope_type": "default",
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"mrope_section": [
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16,
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24,
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24
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],
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"partial_rotary_factor": 1.0,
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"rope_theta": 10000
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},
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"tie_word_embeddings": false,
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"use_cache": true
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},
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"vision_config": {
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"model_type": "glm_ocr_vision",
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"hidden_size": 1024,
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"depth": 24,
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"num_heads": 16,
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"attention_bias": true,
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"intermediate_size": 4096,
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"hidden_act": "silu",
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"hidden_dropout_prob": 0.0,
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"initializer_range": 0.02,
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"image_size": 336,
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"patch_size": 14,
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"out_hidden_size": 1536,
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"rms_norm_eps": 1e-05,
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"spatial_merge_size": 2,
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"temporal_patch_size": 2
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},
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"image_start_token_id": 59256,
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"image_end_token_id": 59257,
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"video_start_token_id": 59258,
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"video_end_token_id": 59259,
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"image_token_id": 59280,
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"video_token_id": 59281,
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"transformers_version": "5.0.1dev0"
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}
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processor_config.json
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{
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"image_processor": {
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"do_convert_rgb": true,
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"do_normalize": true,
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"do_rescale": true,
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"do_resize": true,
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"image_mean": [
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],
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"image_processor_type": "Glm46VImageProcessor",
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"image_std": [
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],
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"merge_size": 2,
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"patch_size": 14,
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"resample": 3,
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"rescale_factor": 0.00392156862745098,
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"size": {
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"longest_edge": 9633792,
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"shortest_edge": 12544
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},
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"temporal_patch_size": 2
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},
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"processor_class": "Glm46VProcessor",
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"video_processor": {
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"do_convert_rgb": true,
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"do_normalize": true,
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"do_rescale": true,
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"do_resize": true,
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"do_sample_frames": true,
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"fps": 2,
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"image_mean": [
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0.48145466,
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],
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"image_std": [
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],
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"max_duration": 300,
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"max_image_size": {
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"longest_edge": 47040000
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},
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"merge_size": 2,
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"num_frames": 16,
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"patch_size": 14,
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"resample": 3,
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"rescale_factor": 0.00392156862745098,
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"return_metadata": false,
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"size": {
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"longest_edge": 9633792,
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"shortest_edge": 12544
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},
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"temporal_patch_size": 2,
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"video_processor_type": "Glm46VVideoProcessor"
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}
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}
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tokenizer_config.json
CHANGED
|
@@ -36,13 +36,12 @@
|
|
| 36 |
"</arg_value>",
|
| 37 |
"/nothink",
|
| 38 |
"<|begin_of_box|>",
|
| 39 |
-
"<|end_of_box|>"
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|
| 40 |
],
|
| 41 |
"is_local": true,
|
| 42 |
"model_max_length": 655380,
|
| 43 |
-
"clean_up_tokenization_spaces": false,
|
| 44 |
-
"do_lower_case": false,
|
| 45 |
-
"model_specific_special_tokens": {},
|
| 46 |
"pad_token": "<|endoftext|>",
|
| 47 |
"padding_side": "left",
|
| 48 |
"processor_class": "Glm46VProcessor",
|
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|
| 36 |
"</arg_value>",
|
| 37 |
"/nothink",
|
| 38 |
"<|begin_of_box|>",
|
| 39 |
+
"<|end_of_box|>",
|
| 40 |
+
"<|image|>",
|
| 41 |
+
"<|video|>"
|
| 42 |
],
|
| 43 |
"is_local": true,
|
| 44 |
"model_max_length": 655380,
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| 45 |
"pad_token": "<|endoftext|>",
|
| 46 |
"padding_side": "left",
|
| 47 |
"processor_class": "Glm46VProcessor",
|