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gptkbp:instanceOf
|
machine learning model format
|
|
gptkbp:canBeBenchmarkedBy
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gptkb:ONNX_Runtime
|
|
gptkbp:canBeConvertedFrom
|
gptkb:TensorFlow
gptkb:Chainer
gptkb:Keras
gptkb:MXNet
gptkb:Caffe2
gptkb:PyTorch
|
|
gptkbp:canBeQuantizedBy
|
gptkb:ONNX_Runtime
|
|
gptkbp:canBeValidatedBy
|
gptkb:ONNX_checker
|
|
gptkbp:canImport
|
gptkb:ONNX_Runtime
gptkb:OpenVINO
gptkb:TensorRT
gptkb:Core_ML
gptkb:Microsoft_ML.NET
|
|
gptkbp:developedBy
|
gptkb:Facebook
gptkb:Microsoft
|
|
gptkbp:enables
|
hardware acceleration
model conversion
cross-platform model deployment
model sharing
|
|
gptkbp:exportedTo
|
gptkb:TensorFlow
gptkb:PyTorch
gptkb:scikit-learn
|
|
gptkbp:fileExtension
|
.onnx
|
|
gptkbp:firstReleased
|
2017
|
|
gptkbp:fullName
|
gptkb:Open_Neural_Network_Exchange_models
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
ONNX models
|
|
gptkbp:license
|
gptkb:MIT_License
|
|
gptkbp:optimizedFor
|
gptkb:ONNX_Runtime
|
|
gptkbp:standardizedBy
|
gptkb:ONNX_community
true
|
|
gptkbp:supports
|
inference
model versioning
deep learning models
custom operators
classical machine learning models
standard operators
training (limited)
|
|
gptkbp:supportsOpsetVersions
|
multiple
|
|
gptkbp:usedBy
|
data scientists
software engineers
AI researchers
|
|
gptkbp:usedFor
|
interoperability between machine learning frameworks
|
|
gptkbp:usedIn
|
cloud services
enterprise applications
mobile devices
edge devices
|
|
gptkbp:visualizes
|
gptkb:Netron
|
|
gptkbp:website
|
https://onnx.ai/
|
|
gptkbp:bfsParent
|
gptkb:ONNX.js
gptkb:TorchServe
gptkb:Unity_Sentis
|
|
gptkbp:bfsLayer
|
6
|