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NVIDIA Deep Learning Examples
NVIDIA Deep Learning Examples
ResNet50 pretrained weights (PyTorch, AMP, ImageNet)
Model
NVIDIA Deep Learning Examples
NVIDIA Deep Learning Examples
ResNet50 pretrained weights (PyTorch, AMP, ImageNet)

ResNet50 ImageNet pretrained weights.

This model is backed by NVIDIA's Plus Plus (++) Promise
to learn more about the quality of the datasets used to train this model.
FieldResponse
Intended Application(s) & Domain(s):Computer vision / classification
Model Type:Object Classification
Intended Users:Intended for users that use models for classification tasks.
Output:Label for Content
Describe how the model works:Input is passed through resnet blocks and then a classifier produces the output.
Name the adversely impacted groups this has been tested to deliver comparable outcomes regardless of:Not Applicable
Technical Limitations:None
Verified to have met prescribed NVIDIA quality standards:Yes
Performance Metrics:Accuracy, Latency, and Throughput
Potential Known Risks:None Known
Recommended Training:https://www.nvidia.com/en-us/on-demand/session/gtcfall22-a41089/
Licensing:https://www.apache.org/licenses/LICENSE-2.0

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