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")# pip install -U transformers accelerate # 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
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Download README.md from orucexe/azocr: direct link, hf CLI and curl.
- Browser
- Download file 459 Bytes
-
https://huggingface.co/orucexe/azocr/resolve/main/README.md
- Command line
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hf download hf://orucexe/azocr/README.md
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curl -L -o README.md https://huggingface.co/orucexe/azocr/resolve/main/README.md
459 Bytes
metadata
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.