Image-Text-to-Text
PEFT
Safetensors
Ukrainian
lora
ocr
handwriting
handwritten-text-recognition
ukrainian
gemma3
vision-language
conversational
Instructions to use VmF0x/lapa-ocr-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use VmF0x/lapa-ocr-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("lapa-llm/lapa-v0.1.2-instruct") model = PeftModel.from_pretrained(base_model, "VmF0x/lapa-ocr-lora") - Notebooks
- Google Colab
- Kaggle
| { | |
| "image_processor": { | |
| "do_convert_rgb": null, | |
| "do_normalize": true, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "image_mean": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "image_processor_type": "Gemma3ImageProcessor", | |
| "image_seq_length": 256, | |
| "image_std": [ | |
| 0.5, | |
| 0.5, | |
| 0.5 | |
| ], | |
| "resample": 2, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": { | |
| "height": 896, | |
| "width": 896 | |
| } | |
| }, | |
| "image_seq_length": 256, | |
| "processor_class": "Gemma3Processor" | |
| } | |