data2vec: A General Framework for Self-supervised Learning in Speech, Vision and Language
Paper • 2202.03555 • Published
Data2Vec-Vision (large-sized model, fine-tuned on ImageNet-1k)
BEiT model pre-trained in a self-supervised fashion and fine-tuned on ImageNet-1k (1,2 million images, 1000 classes) at resolution 224x224. It was introduced in the paper data2vec: A General Framework for Self-supervised Learning in Speech, Vision and Language by Alexei Baevski, Wei-Ning Hsu, Qiantong Xu, Arun Babu, Jiatao Gu, Michael Auli and first released in this repository.
Usage
from mlx_ssl.models import Data2VecVisionForImageClassification
model = Data2VecVisionForImageClassification.from_pretrained(
"mlx-community/data2vec-vision-large-ft1k"
)
- Downloads last month
- 10
Hardware compatibility
Log In to add your hardware
Quantized
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir data2vec-vision-large-ft1k mlx-community/data2vec-vision-large-ft1k