Instructions to use DeepLearner101/ResNet50FTImageNet with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DeepLearner101/ResNet50FTImageNet with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="DeepLearner101/ResNet50FTImageNet") 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("DeepLearner101/ResNet50FTImageNet") model = AutoModelForImageClassification.from_pretrained("DeepLearner101/ResNet50FTImageNet") - Notebooks
- Google Colab
- Kaggle
| date,timestamp,pid,hostname,node_ip,config/lr,config/momentum,config/weight_decay,config/dropout_rate,config/l1_factor,config/epochs,config/epsilon_range,config/step_size,config/gamma,config/early_stopping_tolerance,config/batch_size | |
| 2023-12-02_19-34-38,1701545678.0,1207.0,604447ff31d8,172.28.0.12,6.528309758930517e-05,0.9436072519617928,2.793674713973482e-05,0.23573034780803015,1.2176114539446087e-05,20.0,"(0.003, 0.154, 0.005)",10.0,0.5,10.0,64.0 | |
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