How to use pfpdostudent/deit-tiny-cifar10-lab with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="pfpdostudent/deit-tiny-cifar10-lab") 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("pfpdostudent/deit-tiny-cifar10-lab") model = AutoModelForImageClassification.from_pretrained("pfpdostudent/deit-tiny-cifar10-lab", device_map="auto")
Fine-tuned in Google Colab on a GPU and tracked with MLflow.
facebook/deit-tiny-patch16-224
lr_1e-4
0.9315
0.9435
d8c6e08488204ef38f674d0f0c422162
Files info
Base model
