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
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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
| 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 | |