Instructions to use DeepLearner101/ImageNetSelectedSubsetBasedModel-FineTuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DeepLearner101/ImageNetSelectedSubsetBasedModel-FineTuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="DeepLearner101/ImageNetSelectedSubsetBasedModel-FineTuning") 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/ImageNetSelectedSubsetBasedModel-FineTuning") model = AutoModelForImageClassification.from_pretrained("DeepLearner101/ImageNetSelectedSubsetBasedModel-FineTuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): 4440c03
pytorch_model_0174.pth, training and config files uploaded
Browse files- pytorch_model_0174.pth +3 -0
- training_metrics_0174.json +0 -0
pytorch_model_0174.pth
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training_metrics_0174.json
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