Image-to-Text
Transformers
Safetensors
Sinhala
vision-encoder-decoder
image-text-to-text
ocr
sinhala
handwritten-text-recognition
trocr
Instructions to use hasindu-k/sinhala-handwritten-notes-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hasindu-k/sinhala-handwritten-notes-v3 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="hasindu-k/sinhala-handwritten-notes-v3")# Load model directly from transformers import AutoTokenizer, AutoModelForImageTextToText tokenizer = AutoTokenizer.from_pretrained("hasindu-k/sinhala-handwritten-notes-v3") model = AutoModelForImageTextToText.from_pretrained("hasindu-k/sinhala-handwritten-notes-v3") - Notebooks
- Google Colab
- Kaggle
File size: 456 Bytes
27eb085 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | {
"image_processor": {
"do_normalize": true,
"do_rescale": true,
"do_resize": true,
"image_mean": [
0.5,
0.5,
0.5
],
"image_processor_type": "ViTImageProcessor",
"image_std": [
0.5,
0.5,
0.5
],
"resample": 2,
"rescale_factor": 0.00392156862745098,
"size": {
"height": 384,
"width": 384
}
},
"processor_class": "TrOCRProcessor"
}
|