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
File size: 1,570 Bytes
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"architectures": [
"GlmOcrForConditionalGeneration"
],
"model_type": "glm_ocr",
"text_config": {
"model_type": "glm_ocr_text",
"pad_token_id": 59246,
"vocab_size": 59392,
"eos_token_id": [
59246,
59253
],
"attention_bias": false,
"attention_dropout": 0.0,
"head_dim": 128,
"hidden_act": "silu",
"hidden_size": 1536,
"initializer_range": 0.02,
"intermediate_size": 4608,
"max_position_embeddings": 131072,
"num_attention_heads": 16,
"num_hidden_layers": 16,
"num_nextn_predict_layers": 1,
"num_key_value_heads": 8,
"rms_norm_eps": 1e-05,
"dtype": "bfloat16",
"rope_parameters": {
"rope_type": "default",
"mrope_section": [
16,
24,
24
],
"partial_rotary_factor": 1.0,
"rope_theta": 10000
},
"tie_word_embeddings": false,
"use_cache": true
},
"vision_config": {
"model_type": "glm_ocr_vision",
"hidden_size": 1024,
"depth": 24,
"num_heads": 16,
"attention_bias": true,
"intermediate_size": 4096,
"hidden_act": "silu",
"hidden_dropout_prob": 0.0,
"initializer_range": 0.02,
"image_size": 336,
"patch_size": 14,
"out_hidden_size": 1536,
"rms_norm_eps": 1e-05,
"spatial_merge_size": 2,
"temporal_patch_size": 2
},
"image_start_token_id": 59256,
"image_end_token_id": 59257,
"video_start_token_id": 59258,
"video_end_token_id": 59259,
"image_token_id": 59280,
"video_token_id": 59281,
"transformers_version": "5.0.1dev0"
}
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