Image-to-Text
PEFT
Safetensors
Oriya
odia
ocr
vision-language
qwen2-vl
lora
optical-character-recognition
Instructions to use shantipriya/odia-ocr-qwen-finetuned_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use shantipriya/odia-ocr-qwen-finetuned_v2 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-VL-3B-Instruct") model = PeftModel.from_pretrained(base_model, "shantipriya/odia-ocr-qwen-finetuned_v2") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- 80f2afb31694ceaf79a4b21ea546963acd16b0b6c54d28a2157e9bbaa5496feb
- Size of remote file:
- 241 kB
- SHA256:
- d715c3704adf3143c8ec83a3a62ee50b2e22916d7d08c873812287720297d74b
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