Instructions to use JoshuaKelleyDs/quickdraw-MobileVITV2-2.0-Finetune with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JoshuaKelleyDs/quickdraw-MobileVITV2-2.0-Finetune with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="JoshuaKelleyDs/quickdraw-MobileVITV2-2.0-Finetune") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("JoshuaKelleyDs/quickdraw-MobileVITV2-2.0-Finetune") model = AutoModelForImageClassification.from_pretrained("JoshuaKelleyDs/quickdraw-MobileVITV2-2.0-Finetune", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_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": 28, | |
| "width": 28 | |
| }, | |
| "do_center_crop": true, | |
| "do_convert_rgb": false, | |
| "do_flip_channel_order": false, | |
| "do_rescale": true, | |
| "do_resize": true, | |
| "image_processor_type": "MobileViTImageProcessor", | |
| "resample": 2, | |
| "rescale_factor": 0.00392156862745098, | |
| "size": { | |
| "shortest_edge": 28 | |
| } | |
| } | |