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1>>> from transformers import AutoFeatureExtractor, RegNetModel
2>>> import torch
3>>> from datasets import load_dataset
4
5>>> dataset = load_dataset("huggingface/cats-image")
6>>> image = dataset["test"]["image"][0]
7
8>>> feature_extractor = AutoFeatureExtractor.from_pretrained("zuppif/regnet-y-040")
9>>> model = RegNetModel.from_pretrained("zuppif/regnet-y-040")
10
11>>> inputs = feature_extractor(image, return_tensors="pt")
12
13>>> with torch.no_grad():
14... outputs = model(**inputs)
15
16>>> last_hidden_states = outputs.last_hidden_state
17>>> list(last_hidden_states.shape)
18[1, 1088, 7, 7]