keras_cv_attention_models
Keras beit,caformer,CMT,CoAtNet,convnext,davit,dino,efficientdet,edgenext,efficientformer,efficientnet,eva,fasternet,fastervit,fastvit,flexivit,gcvit,ghostnet,gpvit,hornet,hiera,iformer,inceptionnext,lcnet,levit,maxvit,mobilevit,moganet,nat,nfnets,pvt,swin,tin
Build and evaluate various AI models for tasks like image recognition and detection using Keras.
Claim its page: indexed whatever its rank, translated into six languages, and enriched with what you write yourself.
Get an email alert on its next release or when it starts trending — never miss the moment.
Free · no card · unsubscribe anytimeKeras beit,caformer,CMT,CoAtNet,convnext,davit,dino,efficientdet,edgenext,efficientformer,efficientnet,eva,fasternet,fastervit,fastvit,flexivit,gcvit,ghostnet,gpvit,hornet,hiera,iformer,inceptionnext,lcnet,levit,maxvit,mobilevit,moganet,nat,nfnets,pvt,swin,tin
keras_cv_attention_models has 627 stars on GitHub. It has been forked 97 times. keras_cv_attention_models is written mainly in Python. It has been in active development since 2021. keras_cv_attention_models is available under the MIT license. Its main topics are attention, clip, coco, ddpm.
What is keras_cv_attention_models?
Keras beit,caformer,CMT,CoAtNet,convnext,davit,dino,efficientdet,edgenext,efficientformer,efficientnet,eva,fasternet,fastervit,fastvit,flexivit,gcvit,ghostnet,gpvit,hornet,hiera,iformer,inceptionnext,lcnet,levit,maxvit,mobilevit,moganet,nat,nfnets,pvt,swin,tin
Is keras_cv_attention_models open source?
keras_cv_attention_models is an open-source project. It is released under the MIT license.
Is keras_cv_attention_models free?
Yes. keras_cv_attention_models is free and open source — you can use, modify and self-host it.
What license does keras_cv_attention_models use?
keras_cv_attention_models is available under the MIT license.
What language is keras_cv_attention_models written in?
keras_cv_attention_models is written mainly in Python.
Add this live badge to your README — your GitHub stars and directory rank, refreshed daily.
[](https://olud.ai/project/leondgarse-keras-cv-attention-models.html)
Measured from GitHub topics shared by both projects, weighted by how rare each topic is.