Instructions to use DeepLearner101/ImageNetSubsetForFineTuningBasedModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DeepLearner101/ImageNetSubsetForFineTuningBasedModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="DeepLearner101/ImageNetSubsetForFineTuningBasedModel") 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/ImageNetSubsetForFineTuningBasedModel") model = AutoModelForImageClassification.from_pretrained("DeepLearner101/ImageNetSubsetForFineTuningBasedModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
a9dfebe
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Parent(s): c430aca
Upload hyperparameters_tuning_results.csv with huggingface_hub
Browse files
hyperparameters_tuning_results.csv
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