Convnext Base.dinov3 Lvd1689m is an image feature extraction model hosted on Hugging Face. It belongs to the ConvNeXt Base architecture and carries the dinov3 pretraining. The model is provided by the timm PyTorch Image Models collection and is made available for use in computer vision pipelines that require feature representations from images.
It can be loaded directly through the timm library using the command timm.create_model with the identifier hf_hub:timm/convnext_base.dinov3_lvd1689m and the pretrained flag set to true. The same model is also accessible via the Hugging Face Transformers library, either through a high-level pipeline tagged for image-feature-extraction or by instantiating an AutoModel with the repository name timm/convnext_base.dinov3_lvd1689m and an optional device_map. Model weights are distributed in both PyTorch and Safetensors formats.
The model card references two arXiv papers, 2508.10104 and 2201.03545, that document the underlying methods. It carries the dinov3-license. The entry appears under the Image Feature Extraction task category on the platform. No pricing information is listed because the model is offered as an open download from the public repository.
Convnext Base.dinov3 Lvd1689m sits in PulseGate's Other AI category. It focuses on obtaining high-quality visual embeddings from images using modern ConvNeXt architecture with DINOv3 self-supervised pretraining. It is built as an open-source project for computer vision researchers and developers. Convnext Base.dinov3 Lvd1689m is open source under the Apache-2.0 license. Convnext Base.dinov3 Lvd1689m is available on the web and API.
Behind Convnext Base.dinov3 Lvd1689m is PyTorch Image Models, and the product first shipped in 2019. Development happens publicly on GitHub with 37k stars and 49 commits in the last 90 days. Key capabilities include Image Feature Extraction, Self-Supervised Learning, and timm Integration.
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