uoft-cs/cifar10
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How to use glopez/cifar-10 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("image-classification", model="glopez/cifar-10")
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("glopez/cifar-10")
model = AutoModelForImageClassification.from_pretrained("glopez/cifar-10", device_map="auto")This model is a fine-tuned version of google/vit-base-patch16-224 on the cifar10 dataset.
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The following hyperparameters were used during training: