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:
- 3538451377a436066f96e19c7fc0a89287588837b643dc39a5ac9b71fa9e590d
- Size of remote file:
- 1.19 GB
- SHA256:
- c948e2fad32c581952e15b26ea4f818eaccba239a0a6ffaa052b2402f181136b
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