MetaReleased Dec 2015MIT
We don't benchmark ResNet-34.
It is an open-weight model from Meta under the MIT license, and free for commercial use.
ResNet-34 is a deep residual network for image classification introduced by Kaiming He et al. in December 2015. It is a medium-sized variant in the original ResNet family, designed for ImageNet-scale classification with 34 convolutional layers organized into residual blocks using skip connections. These connections allow the model to learn residual mappings rather than full transformations, mitigating the vanishing gradient problem and enabling stable training of deeper architectures.
ResNet-34 is released under MIT, a permissive license. The ResNet-34 license lets you use, modify, and sell work built on the model, with the copyright notice as the only real obligation and no requirement to open-source related code changes.
MIT grants no explicit patent license and disclaims all warranties. If patent exposure is a concern for your deployment, review it with counsel before launch.
Read the full MIT license ↗No commercial license is needed for ResNet-34: permissive terms let you keep related code private while deploying commercially.
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Talk to salesThis model is released under the MIT License, a short and permissive open-source license that allows commercial use, modification, and redistribution.
Yes. Under the terms of the MIT license, you can freely use this model for commercial purposes. You must retain the copyright notice and license text when redistributing.
License information is provided as a guide and is not legal advice.
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