This open-weight EfficientNet-B0 model is provided through the timm PyTorch Image Models ecosystem for image classification. Developers can load it with timm or Transformers and run inference locally or through supported Hugging Face services.
Tf Efficientnet B0.ns Jft In1k sits in PulseGate's Other AI category. It focuses on running image classification without training an EfficientNet model from scratch. Tf Efficientnet B0.ns Jft In1k is an open-source project aimed at machine-learning developers and computer-vision researchers. Tf Efficientnet B0.ns Jft In1k is open source under the Apache-2.0 license. It ships for the web, the command line, and API, and it can be self-hosted.
It is developed by Ross Wightman / timm, and it first shipped in 2017. Development happens publicly on GitHub with 5.3k stars. Key capabilities include image classification, pretrained weights, and safetensors format. It exposes integrations via a public API.
Summary written by a language model from the project’s public pages.
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