|
gptkbp:instance_of
|
gptkb:software
|
|
gptkbp:aims_to
|
improve inference speed
maintain accuracy
reduce model size
|
|
gptkbp:can_be_used_with
|
gptkb:TF_Hub
gptkb:Keras
gptkb:TF_Estimator
|
|
gptkbp:community_support
|
active community
|
|
gptkbp:developed_by
|
gptkb:Job_Search_Engine
|
|
gptkbp:has
|
sample code
demo applications
example models
|
|
gptkbp:has_documentation
|
online documentation
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
Tensor Flow Model Optimization Toolkit
|
|
gptkbp:includes
|
gptkb:Tensor_Flow_Lite
gptkb:Tensor_Flow_Model_Garden
|
|
gptkbp:is_available_on
|
gptkb:archive
|
|
gptkbp:is_compatible_with
|
gptkb:Graphics_Processing_Unit
|
|
gptkbp:is_integrated_with
|
gptkb:Tensor_Flow_Extended_(TFX)
gptkb:Tensor_Flow.js
gptkb:Tensor_Flow_Hub
gptkb:Tensor_Flow_Serving
|
|
gptkbp:is_open_source
|
gptkb:theorem
|
|
gptkbp:is_part_of
|
machine learning frameworks
open-source AI tools
Google AI initiatives
Tensor Flow ecosystem
|
|
gptkbp:is_supported_by
|
gptkb:smartphone
gptkb:operating_system
|
|
gptkbp:is_used_by
|
data scientists
AI researchers
machine learning engineers
|
|
gptkbp:is_used_for
|
optimizing machine learning models
|
|
gptkbp:provides
|
model compression techniques
AP Is for model optimization
model clustering techniques
model pruning techniques
model quantization techniques
|
|
gptkbp:release_date
|
gptkb:2019
|
|
gptkbp:suitable_for
|
gptkb:mobile_application
edge devices
cloud deployment
|
|
gptkbp:supports
|
model evaluation
quantization
pruning
transfer learning
clustering
|
|
gptkbp:tutorials
|
online tutorials
|
|
gptkbp:written_in
|
gptkb:Library
|
|
gptkbp:bfsParent
|
gptkb:Graphics_Processing_Unit
|
|
gptkbp:bfsLayer
|
3
|