Instructions to use jungjongho/vit-base-DogSick with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jungjongho/vit-base-DogSick with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="jungjongho/vit-base-DogSick") 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("jungjongho/vit-base-DogSick") model = AutoModelForImageClassification.from_pretrained("jungjongho/vit-base-DogSick") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_name_or_path": "google/vit-base-patch16-224-in21k", | |
| "architectures": [ | |
| "ViTForImageClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.0, | |
| "encoder_stride": 16, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.0, | |
| "hidden_size": 768, | |
| "id2label": { | |
| "0": "\uacb0\ub9c9\uc5fc", | |
| "1": "\uada4\uc591\uc131\uac01\ub9c9\uc9c8\ud658", | |
| "10": "\uc720\ub8e8\uc99d", | |
| "11": "\uc815\uc0c1", | |
| "12": "\ud575\uacbd\ud654", | |
| "2": "\ubc31\ub0b4\uc7a5 \ucd08\uae30", | |
| "3": "\ube44\uada4\uc591\uc131\uac01\ub9c9\uc9c8\ud658", | |
| "4": "\ube44\uc131\uc219", | |
| "5": "\uc0c9\uc18c\uce68\ucc29\uc131\uac01\ub9c9\uc5fc", | |
| "6": "\uc131\uc219", | |
| "7": "\uc548\uac80\ub0b4\ubc18\uc99d", | |
| "8": "\uc548\uac80\uc5fc", | |
| "9": "\uc548\uac80\uc885\uc591" | |
| }, | |
| "image_size": 224, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "label2id": { | |
| "\uacb0\ub9c9\uc5fc": "0", | |
| "\uada4\uc591\uc131\uac01\ub9c9\uc9c8\ud658": "1", | |
| "\ubc31\ub0b4\uc7a5 \ucd08\uae30": "2", | |
| "\ube44\uada4\uc591\uc131\uac01\ub9c9\uc9c8\ud658": "3", | |
| "\ube44\uc131\uc219": "4", | |
| "\uc0c9\uc18c\uce68\ucc29\uc131\uac01\ub9c9\uc5fc": "5", | |
| "\uc131\uc219": "6", | |
| "\uc548\uac80\ub0b4\ubc18\uc99d": "7", | |
| "\uc548\uac80\uc5fc": "8", | |
| "\uc548\uac80\uc885\uc591": "9", | |
| "\uc720\ub8e8\uc99d": "10", | |
| "\uc815\uc0c1": "11", | |
| "\ud575\uacbd\ud654": "12" | |
| }, | |
| "layer_norm_eps": 1e-12, | |
| "model_type": "vit", | |
| "num_attention_heads": 12, | |
| "num_channels": 3, | |
| "num_hidden_layers": 12, | |
| "patch_size": 16, | |
| "problem_type": "single_label_classification", | |
| "qkv_bias": true, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.23.1" | |
| } | |