Image-to-Text
Transformers
Safetensors
Azerbaijani
glm_ocr
image-text-to-text
ocr
vision-language
markdown
azerbaijani
Instructions to use orucexe/azocr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use orucexe/azocr 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="orucexe/azocr")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("orucexe/azocr") model = AutoModelForMultimodalLM.from_pretrained("orucexe/azocr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 459 Bytes
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language:
- az
license: apache-2.0
pipeline_tag: image-to-text
tags:
- ocr
- vision-language
- markdown
- azerbaijani
library_name: transformers
---
# AZOCR
Azerbaijani OCR model based on GLM-OCR.
## Training
- Base model: GLM-OCR
- Language: Azerbaijani
- Dataset: 6699 page samples
- Method: LoRA
- GPUs: 2× NVIDIA Tesla T4
- Epochs: 2
## Notes
Fine-tuned for Azerbaijani document OCR.
## How to use?
https://github.com/orucexe/azerbaijani-ocr
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