Upload README.md

README.md

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+---
+license: apache-2.0
+tags:
+- vision
+
+
+
+
+
+---
+
+# RegNetModel
+
+RegNetModel model was introduced in the paper [Self-supervised Pretraining of Visual Features in the Wild](https://arxiv.org/abs/2103.01988) and first released in [this repository](https://github.com/facebookresearch/vissl/tree/main/projects/SEER). 
+
+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.
+
+## Model description
+
+This gigantic model is a scale up [RegNetY](https://arxiv.org/abs/2003.13678) model trained on one bilion random images.
+
+![model image](https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/regnet_architecture.png)
+
+## Intended uses & limitations
+
+You can use the raw model for image classification. See the [model hub](https://huggingface.co/models?search=regnet) to look for
+fine-tuned versions on a task that interests you.
+
+### How to use
+
+Here is how to use this model:
+
+```python
+>>> from transformers import AutoFeatureExtractor, RegNetModel
+>>> 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 = RegNetModel.from_pretrained("facebook/regnet-y-040")
+
+>>> 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](https://huggingface.co/docs/transformers/master/en/model_doc/regnet).