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Aimv2 3B Patch14 336

We introduce the AIMv2 family of vision models pre-trained with a multimodal autoregressive objective. AIMv2 pre-training is simple and straightforward to train and scale effectively. Some AIMv2 highlights include:

KindOtherVersionRevision 321edf4

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Other
File size
864 MB–10.1 GB
Version
vRevision 321edf4
Updated
Sep 21, 2026
Downloads
146
Source
Hugging Face

Source excerpt

We introduce the AIMv2 family of vision models pre-trained with a multimodal autoregressive objective. AIMv2 pre-training is simple and straightforward to train and scale effectively. Some AIMv2 highlights include:

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Hugging FacePrimaryVersion 321edf4fe7e35ccfc2f44346c69888b9bf53ae0d
huggingface.co/apple/aimv2-3B-patch14-336/tree/321edf4fe7e35ccfc2f44346c69888b9bf53ae0d

Verified Sep 9

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flax_model.msgpack

msgpack · 10.1 GB · SHA-256 fb6fa97486ca…5894 · Hugging Face

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mlx_model.safetensors

safetensors · 10.1 GB · SHA-256 ea196b76234d…2fdf · Hugging Face

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model-00001-of-00003.safetensors

safetensors · 4.65 GB · SHA-256 614f908c214c…4b44 · Hugging Face

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model-00002-of-00003.safetensors

safetensors · 4.64 GB · SHA-256 87f2411681b3…2b56 · Hugging Face

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model-00003-of-00003.safetensors

safetensors · 864 MB · SHA-256 663344db6515…b81a · Hugging Face

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Source excerpts

2 excerpts

--- library_name: transformers license: apple-amlr metrics: - accuracy pipeline_tag: image-feature-extraction tags: - vision - image-feature-extraction - mlx - pytorch model-index: - name: aimv2-3B-patch14-336 results: - task: type: classification name: Classification dataset: name: imagenet-1k type: imagenet-1k metrics: - type: accuracy value: 89.2 name: Accuracy verified: false - task: type: classification name: Classification dataset: name: inaturalist-18 type: inaturalist-18 metrics: - type: accuracy value: 84.4 name: Accuracy verified: false - task: type: classification name: Classification dataset: name: cifar10 type: cifar10 metrics: - type: accuracy value: 99.5 name: Accuracy verified: false - task: type: classification name: Classification dataset: name: cifar100 type: cifar100 metrics: - type: accuracy value: 94.4 name: Accuracy verified: false - task: type: classification name: Classification dataset: name: food101 type: food101 metrics: - type: accuracy value: 97.2 name: Accuracy verified: false - task: type: classification name: Classification dataset: name: dtd type: dtd metrics: - type: accuracy value: 89.3 name: Accuracy verified: false - task: type: classification name: Classification dataset: name: oxford-pets type: oxford-pets metrics: - type: accuracy value: 97.2 name: Accuracy verified: false - task: type: classification name: Classification dataset: name: stanford-cars type: stanford-cars metrics: - type: accuracy value: 96.6 name: Accuracy verified: false - task: type: classification name: Classification dataset: name: camelyon17 type: camelyon17 metrics: - type: accuracy value: 93.2 name: Accuracy verified: false - task: type: classification name: Classification dataset: name: patch-camelyon type: patch-camelyon metrics: - type: accuracy value: 89.3 name: Accuracy verified: false - task: type: classification name: Classification dataset: name: rxrx1 type: rxrx1 metrics: - type: accuracy value: 8.8 name: Accuracy verified: false - task: type: classification name: Classification dataset: name: eurosat type: eurosat metrics: - type: accuracy value: 99.0 name: Accuracy verified: false - task: type: classification name: Classification dataset: name: fmow type: fmow metrics: - type: accuracy value:...

Source context: 146 downloads · 6 likes · Pipeline image-feature-extraction · Library transformers · Repo apple/aimv2-3B-patch14-336