facebook/convnextv2-tiny-22k-224
image-classification model by facebook
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Model card & documentation
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ConvNeXt V2 model pretrained using the FCMAE framework and fine-tuned on the ImageNet-22K 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. ConvNeXt V2 is a pure convolutional model (ConvNet) that introduces a fully convolutional masked autoencoder framework (FCMAE) and a new Global Response Normalization (GRN) layer to ConvNeXt. ConvNeXt V2 significantly…
Read the full model card ↗ · Preview checked 2026-10-28T01:20:52.999Z
Inside the original model card — Document outline
- ConvNeXt V2 (tiny-sized model)
- Model description
- Intended uses & limitations
- How to use
- BibTeX entry and citation info
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Documentation belongs to its respective authors. Reported project/model license: apache-2.0. A listing is not a grant of reuse or training rights. Confirm the document’s own terms at the source.
Model overview
facebook/convnextv2-tiny-22k-224 is a image-classification model repository published by facebook on Hugging Face. The source reports the transformers library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- image-classification
- Library
- transformers
- Recent downloads (30 days)
- 107,510
- Cumulative likes
- 10
- Hugging Face trending score
- 0
- Reported safetensors parameters
- 28,635,496
- Architecture
- ConvNextV2ForImageClassification
- License
- apache-2.0
- Access
- Not gated by Hugging Face
- Created
- 2023-02-19T07:33:39.000Z
- Last modified
- 2025-02-17T18:43:28.000Z
Compatibility and lineage
Language coverage was not reported.
Base-model lineage was not included.
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-11-01T06:54:32.747Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.
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