Instructions to use Thamer/resnet-base-fine_tuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Thamer/resnet-base-fine_tuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Thamer/resnet-base-fine_tuned") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("Thamer/resnet-base-fine_tuned") model = AutoModelForImageClassification.from_pretrained("Thamer/resnet-base-fine_tuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Thamer Smadi commited on
Commit ·
2d0ef11
1
Parent(s): 6435e5d
Training in progress, epoch 3
Browse files
pytorch_model.bin
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