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gptkbp:instance_of
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gptkb:machine_learning
|
|
gptkbp:based_on
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gptkb:Transformers
|
|
gptkbp:can_be_used_for
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gptkb:translator
question answering
text generation
summarization
text classification
|
|
gptkbp:collaborated_with
|
academic institutions
industry partners
|
|
gptkbp:designed_for
|
few-shot learning
|
|
gptkbp:developed_by
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gptkb:Google_Research
|
|
gptkbp:has_achieved
|
state-of-the-art results
|
|
gptkbp:has_applications_in
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gptkb:customer_service
gptkb:education
healthcare
finance
content creation
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
FLAN family of models
|
|
gptkbp:improves
|
task performance
|
|
gptkbp:includes
|
gptkb:FLAN-T5
FLAN-Pa LM
|
|
gptkbp:is_available_on
|
gptkb:Google_Cloud
|
|
gptkbp:is_discussed_in
|
AI conferences
|
|
gptkbp:is_documented_in
|
research papers
|
|
gptkbp:is_enhanced_by
|
fine-tuning
|
|
gptkbp:is_evaluated_by
|
human feedback
benchmark datasets
bias and fairness
|
|
gptkbp:is_influenced_by
|
gptkb:GPT_models
|
|
gptkbp:is_optimized_for
|
efficiency
|
|
gptkbp:is_part_of
|
AI ethics discussions
AI research community
AI model lifecycle management
AI model deployment strategies
AI model evaluation frameworks
AI model monitoring systems
|
|
gptkbp:is_related_to
|
language models
|
|
gptkbp:is_scalable
|
large datasets
|
|
gptkbp:is_supported_by
|
gptkb:Tensor_Flow
gptkb:Py_Torch
|
|
gptkbp:is_tested_for
|
gptkb:security
safety
robustness
generalization
|
|
gptkbp:is_trained_in
|
diverse datasets
|
|
gptkbp:is_used_in
|
gptkb:academic_research
industry applications
|
|
gptkbp:is_used_to
|
automate tasks
improve user experience
drive innovation
support decision making
enhance productivity
|
|
gptkbp:performance
|
other models
|
|
gptkbp:released_in
|
gptkb:2022
|
|
gptkbp:supports
|
multiple languages
|
|
gptkbp:uses
|
natural language processing
|
|
gptkbp:utilizes
|
transfer learning
|
|
gptkbp:bfsParent
|
gptkb:FLAN-T5
|
|
gptkbp:bfsLayer
|
6
|