Dinov2 Base is a base-sized vision transformer model trained using DINOv2 for image feature extraction. Hosted on Hugging Face by AI at Meta, it belongs to the class of vision transformers and is distributed with open weights under the Apache-2.0 license.
The model supports direct use through the Transformers library. Code examples show loading it via a high-level pipeline for image-feature-extraction or by importing AutoImageProcessor and AutoModel from_pretrained with the identifier facebook/dinov2-base. It is provided in PyTorch and Safetensors formats.
Intended for computer vision researchers and developers, the model is accompanied by a model card that includes a description, intended uses and limitations, how-to-use guidance, and citation information referencing arXiv:2304.07193. It can be deployed through Hugging Face inference providers, notebooks such as Google Colab and Kaggle, or local applications.
The repository lists it among collections for image feature extraction and includes community contributions along with options to copy the model to a bucket or follow updates from the maintainer.
Dinov2 Base is an Other AI product. It focuses on extracting robust image features for computer vision tasks using a transformer-based model. It is built as an open-source project for computer vision researchers and developers. Dinov2 Base is open source under the Open Source license. The product ships for the web, the command line, and API, and it can be self-hosted.
Meta AI builds and maintains Dinov2 Base, and the product first shipped in 2023. Key capabilities include image feature extraction, vision transformer, and representation learning.
Latest indexed changes and source events
facebook/dinov2-base verified by the PulseGate indexer
Other apps tracked under the same category.
