KerasHub: Pretrained Models / API documentation / KerasHub Model Architectures

KerasHub Model Architectures

The following is a list of model architectures supported by KerasHub. These models can be created in two ways:

  • Through the from_preset() constructor, which instantiates an object with a pre-trained configurations, vocabularies, and weights.
  • Through custom configuration controlled by the user.

For the full list of available pretrained model presets shipped directly by the Keras team, see the Pretrained Models page.

Albert

Bart

BASNet

Bert

Bloom

CLIP

CSPNet

D-FINE

DebertaV3

DeepLabV3

DeiT

DenseNet

DepthAnything

DINOV2

DistilBert

EfficientNet

Electra

ESM

Falcon

Flux

FNet

Gemma

Gemma3

GPT2

GPT-NeoX

HGNetV2

Llama

Llama3

Mistral

MiT

Mixtral

MobileNet

MobileNetV5

Moonshine

OPT

PaliGemma

PARSeq

Phi3

Qwen

Qwen3

Qwen3Moe

QwenMoe

ResNet

RetinaNet

Roberta

SegFormer

Segment Anything Model

SigLIP

SmolLM3

Stable Diffusion 3

T5

T5Gemma

VGG

ViT

ViTDet

Whisper

Xception

XLNet

XLMRoberta