Statements (50)
| Predicate | Object |
|---|---|
| gptkbp:instance_of |
gptkb:language
|
| gptkbp:bfsLayer |
5
|
| gptkbp:bfsParent |
gptkb:Turing-NLG
|
| gptkbp:allows |
context understanding
factual accuracy bias in training data resource intensive |
| gptkbp:application |
content creation
sentiment analysis chatbots summarization |
| gptkbp:architectural_style |
gptkb:Transformers_character
|
| gptkbp:developed_by |
gptkb:Microsoft
|
| gptkbp:future_plans |
improving efficiency
better contextual understanding reducing bias enhancing multilingual capabilities |
| gptkbp:has_ability |
language translation
natural language understanding question answering text generation |
| https://www.w3.org/2000/01/rdf-schema#label |
Turing-NLG 2.0
|
| gptkbp:impact |
gptkb:Research_Institute
human-computer interaction machine learning applications natural language processing |
| gptkbp:is_evaluated_by |
gptkb:BLEU
Perplexity ROUGE |
| gptkbp:language |
gptkb:French
gptkb:Italian gptkb:Spanish gptkb:Native_American_tribe English |
| gptkbp:orbital_period |
17 billion
|
| gptkbp:performance |
state-of-the-art
|
| gptkbp:provides_information_on |
large text corpora
|
| gptkbp:related_to |
gptkb:GPT-3
gptkb:BERT transformer models XL Net |
| gptkbp:release_date |
gptkb:2021
|
| gptkbp:successor |
gptkb:Turing-NLG
|
| gptkbp:training |
unsupervised learning
supervised fine-tuning |
| gptkbp:use_case |
gptkb:literary_work
gptkb:railway_line data analysis educational tools virtual assistants |