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")# Load model directly from transformers import AutoTokenizer, AutoModelForImageTextToText tokenizer = AutoTokenizer.from_pretrained("zai-org/GLM-OCR") model = AutoModelForImageTextToText.from_pretrained("zai-org/GLM-OCR") - Inference
- Notebooks
- Google Colab
- Kaggle
Add ParseBench evaluation results
#53
by boyang-runllama - opened
This PR ensures your model shows up at https://huggingface.co/datasets/llamaindex/ParseBench.
This is based on the new evaluation results feature: https://huggingface.co/docs/hub/eval-results.
Note: this includes per-dimension performance across all 5 ParseBench dimensions (text_content, text_formatting, layout, chart, table) along with the overall mean score.