Image-Text-to-Text
PEFT
Safetensors
Arabic
arabic
handwriting-recognition
htr
ocr
qlora
vision-language-model
conversational
Eval Results (legacy)
Instructions to use mabdulaziz499/Warraq-Arabic-HTR-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use mabdulaziz499/Warraq-Arabic-HTR-7B with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("QCRI/Fanar-2-Oryx-IVU") model = PeftModel.from_pretrained(base_model, "mabdulaziz499/Warraq-Arabic-HTR-7B") - Notebooks
- Google Colab
- Kaggle
Download assets/cer_comparison.png from mabdulaziz499/Warraq-Arabic-HTR-7B: direct link, hf CLI and curl.
- Browser
- Download file 111 kB
-
https://huggingface.co/mabdulaziz499/Warraq-Arabic-HTR-7B/resolve/main/assets/cer_comparison.png
- Command line
-
hf download hf://mabdulaziz499/Warraq-Arabic-HTR-7B/assets/cer_comparison.png
-
curl -L -o cer_comparison.png https://huggingface.co/mabdulaziz499/Warraq-Arabic-HTR-7B/resolve/main/assets/cer_comparison.png
111 kB

- Xet hash:
- 06dd683c4f81aed0fedb076fbd1ead991e162fa335655cba26fe613772671f92
- Size of remote file:
- 111 kB
- SHA256:
- 383a755e4febecad74f6e1bd99ff859e4810db8a607bfdc8930d22e473cb5dfa
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