Instructions to use hf-tiny-model-private/tiny-random-MobileNetV1Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-MobileNetV1Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="hf-tiny-model-private/tiny-random-MobileNetV1Model")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-tiny-model-private/tiny-random-MobileNetV1Model") model = AutoModel.from_pretrained("hf-tiny-model-private/tiny-random-MobileNetV1Model") - Notebooks
- Google Colab
- Kaggle
| { | |
| "architectures": [ | |
| "MobileNetV1Model" | |
| ], | |
| "classifier_dropout_prob": 0.1, | |
| "depth_multiplier": 0.25, | |
| "hidden_act": "relu6", | |
| "image_size": 32, | |
| "initializer_range": 0.02, | |
| "layer_norm_eps": 0.001, | |
| "min_depth": 8, | |
| "model_type": "mobilenet_v1", | |
| "num_channels": 3, | |
| "tf_padding": true, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.28.0.dev0" | |
| } | |