Instructions to use sgonzalez2000/dermai-efficientnet-b0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sgonzalez2000/dermai-efficientnet-b0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="sgonzalez2000/dermai-efficientnet-b0") 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("sgonzalez2000/dermai-efficientnet-b0") model = AutoModelForImageClassification.from_pretrained("sgonzalez2000/dermai-efficientnet-b0") - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "EfficientNetForImageClassification" | |
| ], | |
| "batch_norm_eps": 0.001, | |
| "batch_norm_momentum": 0.99, | |
| "depth_coefficient": 1.0, | |
| "depth_divisor": 8, | |
| "depthwise_padding": [], | |
| "drop_connect_rate": 0.2, | |
| "dropout_rate": 0.2, | |
| "dtype": "float32", | |
| "expand_ratios": [ | |
| 1, | |
| 6, | |
| 6, | |
| 6, | |
| 6, | |
| 6, | |
| 6 | |
| ], | |
| "hidden_act": "swish", | |
| "hidden_dim": 1280, | |
| "id2label": { | |
| "0": "akiec", | |
| "1": "bcc", | |
| "2": "bkl", | |
| "3": "df", | |
| "4": "mel", | |
| "5": "nv", | |
| "6": "vasc" | |
| }, | |
| "image_size": 224, | |
| "in_channels": [ | |
| 32, | |
| 16, | |
| 24, | |
| 40, | |
| 80, | |
| 112, | |
| 192 | |
| ], | |
| "initializer_range": 0.02, | |
| "kernel_sizes": [ | |
| 3, | |
| 3, | |
| 5, | |
| 3, | |
| 5, | |
| 5, | |
| 3 | |
| ], | |
| "label2id": { | |
| "akiec": 0, | |
| "bcc": 1, | |
| "bkl": 2, | |
| "df": 3, | |
| "mel": 4, | |
| "nv": 5, | |
| "vasc": 6 | |
| }, | |
| "model_type": "efficientnet", | |
| "num_block_repeats": [ | |
| 1, | |
| 2, | |
| 2, | |
| 3, | |
| 3, | |
| 4, | |
| 1 | |
| ], | |
| "num_channels": 3, | |
| "num_hidden_layers": 64, | |
| "out_channels": [ | |
| 16, | |
| 24, | |
| 40, | |
| 80, | |
| 112, | |
| 192, | |
| 320 | |
| ], | |
| "out_features": null, | |
| "pooling_type": "mean", | |
| "squeeze_expansion_ratio": 0.25, | |
| "stage_names": [ | |
| "stem", | |
| "stage1", | |
| "stage2", | |
| "stage3", | |
| "stage4", | |
| "stage5", | |
| "stage6", | |
| "stage7" | |
| ], | |
| "strides": [ | |
| 1, | |
| 2, | |
| 2, | |
| 2, | |
| 1, | |
| 2, | |
| 1 | |
| ], | |
| "transformers_version": "5.12.1", | |
| "width_coefficient": 1.0 | |
| } | |