Image-to-Text
Transformers
PyTorch
TensorBoard
vision-encoder-decoder
image-text-to-text
Generated from Trainer
Instructions to use larabe/testt1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use larabe/testt1 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="larabe/testt1")# Load model directly from transformers import AutoTokenizer, AutoModelForImageTextToText tokenizer = AutoTokenizer.from_pretrained("larabe/testt1") model = AutoModelForImageTextToText.from_pretrained("larabe/testt1") - Notebooks
- Google Colab
- Kaggle
File size: 420 Bytes
b48e74a | 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 27 | {
"do_align_long_axis": false,
"do_normalize": true,
"do_pad": true,
"do_rescale": true,
"do_resize": true,
"do_thumbnail": true,
"image_mean": [
0.5,
0.5,
0.5
],
"image_processor_type": "DonutImageProcessor",
"image_std": [
0.5,
0.5,
0.5
],
"processor_class": "DonutProcessor",
"resample": 2,
"rescale_factor": 0.00392156862745098,
"size": [
720,
960
]
}
|