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Convert your datasets to the tf.data.Dataset format using the [~datasets.Dataset.to_tf_dataset] and the [DefaultDataCollator]:
from transformers import DefaultDataCollator
data_collator = DefaultDataCollator(return_tensors="tf")
tf_train_dataset = train_ds.to_tf_dataset(
columns=["pixel_values", "label"],
shuffle=True,
batch_size=batch_size,
collate_fn=data_collator,
)
tf_eval_dataset = test_ds.to_tf_dataset(
columns=["pixel_values", "label"],
shuffle=True,
batch_size=batch_size,
collate_fn=data_collator,
)
To compute the accuracy from the predictions and push your model to the 🤗 Hub, use Keras callbacks. |