Instructions to use fatzetob/Ponti_Object_Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TF-Keras
How to use fatzetob/Ponti_Object_Classification with TF-Keras:
# Note: 'keras<3.x' or 'tf_keras' must be installed (legacy) # See https://github.com/keras-team/tf-keras for more details. from huggingface_hub import from_pretrained_keras model = from_pretrained_keras("fatzetob/Ponti_Object_Classification") - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "VGG16ForImageClassification" | |
| ], | |
| "downsample_in_first_stage": false, | |
| "id2label": { | |
| "0": "Abfahrtsstange", | |
| "1": "Durchfahrt", | |
| "2": "Pfeiler", | |
| "3": "Ziellandung" | |
| }, | |
| "label2id": { | |
| "Abfahrtsstange": "0", | |
| "Durchfahrt": "1", | |
| "Pfeiler": "2", | |
| "Ziellandung": "3" | |
| }, | |
| "model_type": "vgg16", | |
| "num_channels": 3, | |
| "transformers_version": "4.18.0.dev0" | |
| } | |