|
gptkbp:instance_of
|
gptkb:Transformers
|
|
gptkbp:can
|
up to 4096 tokens
|
|
gptkbp:designed_for
|
long documents
|
|
gptkbp:developed_by
|
gptkb:Facebook_AI_Research
|
|
gptkbp:has
|
multi-head attention
|
|
gptkbp:has_achieved
|
state-of-the-art results
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
Longformer
|
|
gptkbp:improves
|
scalability
|
|
gptkbp:introduced_in
|
gptkb:2020
|
|
gptkbp:is_applied_in
|
question answering
language modeling
summarization
text classification
|
|
gptkbp:is_available_on
|
gptkb:Hugging_Face_Model_Hub
|
|
gptkbp:is_based_on
|
gptkb:BERT
|
|
gptkbp:is_compatible_with
|
gptkb:Tensor_Flow
gptkb:Py_Torch
|
|
gptkbp:is_considered_as
|
a breakthrough in NLP
a model for future research
a model for practical applications
|
|
gptkbp:is_documented_in
|
gptkb:academic_journals
|
|
gptkbp:is_evaluated_by
|
gptkb:SQu_AD_benchmark
gptkb:Long_Range_Arena
gptkb:GLUE_benchmark
|
|
gptkbp:is_influenced_by
|
gptkb:GPT_architecture
Transformer architecture
BERT architecture
|
|
gptkbp:is_known_for
|
improving performance
reducing computational cost
handling long sequences
|
|
gptkbp:is_optimized_for
|
memory efficiency
|
|
gptkbp:is_part_of
|
AI applications
machine learning frameworks
AI research community
transformer family
NLP toolkits
|
|
gptkbp:is_related_to
|
gptkb:neural_networks
deep learning
attention mechanism
|
|
gptkbp:is_supported_by
|
gptkb:academic_research
community contributions
open-source projects
|
|
gptkbp:is_trained_in
|
large datasets
|
|
gptkbp:is_used_by
|
gptkb:developers
gptkb:researchers
data scientists
|
|
gptkbp:is_used_in
|
natural language processing
sentiment analysis
chatbots
information retrieval
virtual assistants
content generation
|
|
gptkbp:supports
|
transfer learning
self-attention
|
|
gptkbp:uses
|
sparse attention mechanism
|
|
gptkbp:bfsParent
|
gptkb:GLUE_benchmark
|
|
gptkbp:bfsLayer
|
5
|