Image-to-Text
Transformers
ONNX
Safetensors
vision-encoder-decoder
image-text-to-text
image-captioning
Instructions to use tarekziade/deit-tiny-distilgpt2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tarekziade/deit-tiny-distilgpt2 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="tarekziade/deit-tiny-distilgpt2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("tarekziade/deit-tiny-distilgpt2") model = AutoModelForMultimodalLM.from_pretrained("tarekziade/deit-tiny-distilgpt2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 424 Bytes
97ad45b | 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 28 | {
"crop_size": {
"height": 224,
"width": 224
},
"do_center_crop": true,
"do_normalize": true,
"do_rescale": true,
"do_resize": true,
"image_mean": [
0.485,
0.456,
0.406
],
"image_processor_type": "DeiTFeatureExtractor",
"image_std": [
0.229,
0.224,
0.225
],
"resample": 3,
"rescale_factor": 0.00392156862745098,
"size": {
"height": 224,
"width": 224
}
}
|