>>> from transformers import AutoFeatureExtractor, RegNetForImageClassification
>>> import torch
>>> from datasets import load_dataset

>>> dataset = load_dataset("huggingface/cats-image")
>>> image = dataset["test"]["image"][0]

>>> feature_extractor = AutoFeatureExtractor.from_pretrained("facebook/regnet-y-040")
>>> model = RegNetForImageClassification.from_pretrained("facebook/regnet-y-040")

>>> inputs = feature_extractor(image, return_tensors="pt")

>>> with torch.no_grad():
...     logits = model(**inputs).logits

>>> # model predicts one of the 1000 ImageNet classes
>>> predicted_label = logits.argmax(-1).item()
>>> print(model.config.id2label[predicted_label])
'tabby, tabby cat'

For more code examples, we refer to the documentation.

facebook/regnet-y-10b-seer-in1k

RegNetY 10B

Intended uses & limitations

How to use

facebook/
regnet-y-10b-seer-in1k