Instructions to use JoshuaKelleyDs/test1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JoshuaKelleyDs/test1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="JoshuaKelleyDs/test1") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("JoshuaKelleyDs/test1") model = AutoModelForImageClassification.from_pretrained("JoshuaKelleyDs/test1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 607 Bytes
2cf5bcb | 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 29 30 31 32 | {
"_valid_processor_keys": [
"images",
"segmentation_maps",
"do_resize",
"size",
"resample",
"do_rescale",
"rescale_factor",
"do_center_crop",
"crop_size",
"do_flip_channel_order",
"return_tensors",
"data_format",
"input_data_format"
],
"crop_size": {
"height": 224,
"width": 224
},
"do_center_crop": true,
"do_flip_channel_order": true,
"do_rescale": true,
"do_resize": true,
"image_processor_type": "MobileViTImageProcessor",
"resample": 2,
"rescale_factor": 0.00392156862745098,
"size": {
"shortest_edge": 224
}
}
|