This gigantic model is a scale up RegNetY model trained on one billion uncurated Instagram images.
Disclaimer: The team releasing RegNetModel did not write a model card for this model so this model card has been written by the Hugging Face team.
You can use the raw model for image classification. See the model hub to look for fine-tuned versions on a task that interests you.
Here is how to use this model:
from transformers import AutoFeatureExtractor, RegNetModel import torch from datasets import load_dataset dataset = load_dataset("huggingface/cats-image") image = dataset["test"]["image"] feature_extractor = AutoFeatureExtractor.from_pretrained("facebook/regnet-y-10b-seer") model = RegNetModel.from_pretrained("facebook/regnet-y-10b-seer") inputs = feature_extractor(image, return_tensors="pt") with torch.no_grad(): outputs = model(**inputs) last_hidden_states = outputs.last_hidden_state list(last_hidden_states.shape) [1, 1088, 7, 7]
For more code examples, we refer to the documentation.
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