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Open Source Model Profile · facebook

convnextv2-atto-1k-224

Convnextv2-atto-1k-224 is a 3.71M-parameter Facebook ConvNeXt V2 image classifier. According to the model card, it is fine-tuned on ImageNet-1K at 224x224 resolution.

Publisher
facebook
Task
image-classification
Model type
convnextv2
License
apache-2.0
Library
transformers
Publication status
Approved for indexing

Model overview

Convnextv2-atto-1k-224 is published by Facebook as an image-classification model. Captured configuration identifies ConvNextV2ForImageClassification with model type convnextv2, and Safetensors metadata reports 3,708,400 parameters. According to the model card, it was pretrained with the FCMAE framework and fine-tuned on ImageNet-1K at 224x224 resolution.

Recorded capabilities

ImageNet-1K classification at 224x224

According to the model card, this atto-sized variant is fine-tuned on ImageNet-1K at 224x224 resolution for raw image-classification use.

Compact 3.71M-parameter ConvNet

Captured configuration identifies ConvNextV2ForImageClassification, with Safetensors metadata reporting 3,708,400 parameters.

Transformers classification workflow

According to the model card, the model classifies images into ImageNet classes with AutoImageProcessor and ConvNextV2ForImageClassification.

Use cases in the source record

  • Lightweight raw image classification into ImageNet classes, using the documented Transformers processor and model classes.

Limitations and unknowns

  • No evaluation results were extracted from this record.
  • The model card notes it was written by the Hugging Face team, not the original ConvNeXt V2 release team.
  • Provider state is historical snapshot data, not independently refreshed current availability.

Source and provenance

Source: facebook/convnextv2-atto-1k-224

Captured: Unknown. Processed: 2026-09-07T19:34:44.204088+00:00.

ConvNeXt V2 (atto-sized model) ConvNeXt V2 model pretrained using the FCMAE framework and fine-tuned on the ImageNet-1K dataset at resolution 224x224. It was introduced in the paper ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders by Woo et al. and first released in this repository . Disclaimer: The team releasing ConvNeXT V2 did not write a model card for this model so this model card has been written by the Hugging Face team. Model description ConvNeXt V2 is a pure convolutional model (ConvNet) that introduces a fully convolutional masked autoencoder framework (FCMAE) and a new Global Response Normalization…

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