UkrainianCatholicUniversity/rukopys
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How to use eldrar/cyrillic-large-handwritten-uk-rykopys with Transformers:
# Use a pipeline as a high-level helper
# Warning: Pipeline type "image-to-text" is no longer supported in transformers v5.
# You must load the model directly (see below) or downgrade to v4.x with:
# 'pip install "transformers<5.0.0'
from transformers import pipeline
pipe = pipeline("image-to-text", model="eldrar/cyrillic-large-handwritten-uk-rykopys") # Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM
tokenizer = AutoTokenizer.from_pretrained("eldrar/cyrillic-large-handwritten-uk-rykopys")
model = AutoModelForMultimodalLM.from_pretrained("eldrar/cyrillic-large-handwritten-uk-rykopys", device_map="auto")Line-level handwritten text recognition for Ukrainian. A TrOCR-style vision-encoder-decoder fine-tuned from Kansallisarkisto/cyrillic-large-handwritten on the RUKOPYS dataset.
from transformers import TrOCRProcessor, VisionEncoderDecoderModel
from PIL import Image
model_name = "eldrar/cyrillic-large-handwritten-uk-rukopys"
processor = TrOCRProcessor.from_pretrained(model_name)
model = VisionEncoderDecoderModel.from_pretrained(model_name)
image = Image.open("line.jpg")
pixel_values = processor(image, return_tensors="pt").pixel_values
ids = model.generate(pixel_values)
print(processor.batch_decode(ids, skip_special_tokens=True)[0])
Base model
Kansallisarkisto/cyrillic-large-stage1