Instructions to use sooks/idbwtiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sooks/idbwtiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="sooks/idbwtiny") 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("sooks/idbwtiny") model = AutoModelForImageClassification.from_pretrained("sooks/idbwtiny") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_name_or_path": "facebook/convnext-tiny-224", | |
| "architectures": [ | |
| "ConvNextForImageClassification" | |
| ], | |
| "depths": [ | |
| 3, | |
| 3, | |
| 9, | |
| 3 | |
| ], | |
| "drop_path_rate": 0.0, | |
| "hidden_act": "gelu", | |
| "hidden_sizes": [ | |
| 96, | |
| 192, | |
| 384, | |
| 768 | |
| ], | |
| "id2label": { | |
| "0": "AI", | |
| "1": "Human" | |
| }, | |
| "image_size": 224, | |
| "initializer_range": 0.02, | |
| "label2id": { | |
| "AI": "0", | |
| "Human": "1" | |
| }, | |
| "layer_norm_eps": 1e-12, | |
| "layer_scale_init_value": 1e-06, | |
| "model_type": "convnext", | |
| "num_channels": 3, | |
| "num_stages": 4, | |
| "out_features": [ | |
| "stage4" | |
| ], | |
| "out_indices": [ | |
| 4 | |
| ], | |
| "patch_size": 4, | |
| "problem_type": "single_label_classification", | |
| "stage_names": [ | |
| "stem", | |
| "stage1", | |
| "stage2", | |
| "stage3", | |
| "stage4" | |
| ], | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.38.2" | |
| } | |