convnext-base-384

Model overview

convnext-base-384 is published by facebook as an image-classification model. The captured configuration identifies ConvNextForImageClassification with model type convnext. According to the model card, it is a base-sized ConvNeXT model trained on ImageNet-1k at 384x384.

Recorded capabilities

Use cases in the source record

• Raw image classification into 1,000 ImageNet classes using the documented Transformers processor and model workflow.
• Starting point for task-specific fine-tuning discovered through the model hub.

Limitations and unknowns

• No parameter count was extracted from this record.
• No evaluation results were extracted from this record.
• Model-card performance language is a publisher claim and was not independently verified.
• Provider state is historical snapshot data, not independently refreshed current availability.

Source and provenance

Source: facebook/convnext-base-384

Captured: Unknown. Processed: 2026-09-07T19:34:44.380182+00:00.

ConvNeXT (base-sized model) ConvNeXT model trained on ImageNet-1k at resolution 384x384. It was introduced in the paper A ConvNet for the 2020s by Liu et al. and first released in this repository . Disclaimer: The team releasing ConvNeXT did not write a model card for this model so this model card has been written by the Hugging Face team. Model description ConvNeXT is a pure convolutional model (ConvNet), inspired by the design of Vision Transformers, that claims to outperform them. The authors started from a ResNet and "modernized" its design by taking the Swin Transformer as inspiration. Intended uses & limitations You can use th…