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:
- fbe0934780f7783e6c9a1cddbf89053201d56d969f35dfebe1cdc7707ced23a6
- Size of remote file:
- 2.38 GB
- SHA256:
- d6927201b5fe9c21263623df8637c605c8fab2b33e0481a93d1dd8ee54616b91
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