Transformer-XL - Revision history

BPeat at 17:38, 3 May 2023

2023-05-03T17:38:55Z

2023-04-28T19:39:21Z

2023-03-19T15:20:40Z

2019-06-30T12:14:52Z

2019-06-29T18:54:45Z

2019-02-28T03:29:23Z

2019-02-02T23:15:58Z

2019-01-19T21:49:08Z

2019-01-19T21:42:27Z

2019-01-19T21:40:14Z

@@ Line 8: / Line 8: @@
 [http://www.google.com/search?q=Transformer+XL+attention+model+deep+machine+learning+ML ...Google search]
-* [[Bidirectional Encoder Representations from Transformers (BERT)]]
+* [[Attention]] Mechanism  ...[[Transformer]] ...[[Generative Pre-trained Transformer (GPT)]] ... [[Generative Adversarial Network (GAN)|GAN]] ... [[Bidirectional Encoder Representations from Transformers (BERT)|BERT]]
 * [http://medium.com/dair-ai/a-light-introduction-to-transformer-xl-be5737feb13 A Light Introduction to Transformer-XL | Elvis - Medium]
 * [http://towardsdatascience.com/transformer-xl-explained-combining-transformers-and-rnns-into-a-state-of-the-art-language-model-c0cfe9e5a924 Transformer-XL Explained: Combining Transformers and RNNs into a State-of-the-art Language Model | Rani Horev - Towards Data Science]
@@ Line 15: / Line 15: @@
 * [[Memory Networks]]
 * [[Autoencoder (AE) / Encoder-Decoder]]

@@ Line 12: / Line 12: @@
 * [http://towardsdatascience.com/transformer-xl-explained-combining-transformers-and-rnns-into-a-state-of-the-art-language-model-c0cfe9e5a924 Transformer-XL Explained: Combining Transformers and RNNs into a State-of-the-art Language Model | Rani Horev - Towards Data Science]
 * [http://openreview.net/forum?id=HJePno0cYm Transformer-XL: Language Modeling with Longer-Term Dependency | Z. Dai, Z. Yang, Y. Yang, W.W. Cohen, J. Carbonell, Quoc V. Le, ad R. Salakhutdinov]
-* [[Natural Language Processing (NLP)]]
+* [[Large Language Model (LLM)]] ... [[Natural Language Processing (NLP)]]  ...[[Natural Language Generation (NLG)|Generation]] ... [[Natural Language Classification (NLC)|Classification]] ...  [[Natural Language Processing (NLP)#Natural Language Understanding (NLU)|Understanding]] ... [[Language Translation|Translation]] ... [[Natural Language Tools & Services|Tools & Services]]
 * [[Memory Networks]]
 * [[Autoencoder (AE) / Encoder-Decoder]]

@@ Line 15: / Line 15: @@
 * [[Memory Networks]]
 * [[Autoencoder (AE) / Encoder-Decoder]]
+* [[Attention]] Mechanism  ...[[Transformer]] Model   ...[[Generative Pre-trained Transformer (GPT)]]

@@ Line 19: / Line 19: @@
 Combines the two leading architectures for language modeling:
-# [[Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and Recurrent Neural Network (RNN)]] to handles the input tokens — words or characters — one by one to learn the relationship between them
+# [[Recurrent Neural Network (RNN)]] to handles the input tokens — words or characters — one by one to learn the relationship between them
 # [[Attention]] Mechanism/[[Transformer]] Model to receive a segment of tokens and learns the dependencies between at once them using an attention mechanism.

@@ Line 20: / Line 20: @@
 Combines the two leading architectures for language modeling:
 # [[Long Short-Term Memory (LSTM), Gated Recurrent Unit (GRU), and Recurrent Neural Network (RNN)]] to handles the input tokens — words or characters — one by one to learn the relationship between them
-# [[Attention Mechanism/Model - Transformer Model]] to receive a segment of tokens and learns the dependencies between at once them using an attention mechanism.
+# [[Attention]] Mechanism/[[Transformer]] Model to receive a segment of tokens and learns the dependencies between at once them using an attention mechanism.
 [http://towardsdatascience.com/transformer-xl-explained-combining-transformers-and-rnns-into-a-state-of-the-art-language-model-c0cfe9e5a924 Transformer-XL Explained: Combining Transformers and RNNs into a State-of-the-art Language Model; Summary of “Transformer-XL: Attentive Language Models Beyond a Fixed-Length Context” | Rani Horev - Towards Data Science]

← Older revision		Revision as of 23:15, 2 February 2019
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		+	{{#seo:
		+	\|title=PRIMO.ai
		+	\|titlemode=append
		+	\|keywords=artificial, intelligence, machine, learning, models, algorithms, data, singularity, moonshot, Tensorflow, Google, Nvidia, Microsoft, Azure, Amazon, AWS
		+	\|description=Helpful resources for your journey with artificial intelligence; videos, articles, techniques, courses, profiles, and tools
		+	}}
	[http://www.youtube.com/results?search_query=Transformer-XL+attention+model+ai+deep+learning+model YouTube search...]		[http://www.youtube.com/results?search_query=Transformer-XL+attention+model+ai+deep+learning+model YouTube search...]
	[http://www.google.com/search?q=Transformer+XL+attention+model+deep+machine+learning+ML ...Google search]		[http://www.google.com/search?q=Transformer+XL+attention+model+deep+machine+learning+ML ...Google search]

← Older revision		Revision as of 21:49, 19 January 2019
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	<youtube>yCdl2afW88k</youtube>		<youtube>yCdl2afW88k</youtube>
		+	<youtube>cgrqWBWzKjI</youtube>

← Older revision		Revision as of 21:40, 19 January 2019
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	* [[Memory Networks]]		* [[Memory Networks]]
	* [[Autoencoder (AE) / Encoder-Decoder]]		* [[Autoencoder (AE) / Encoder-Decoder]]
		+	* [http://openreview.net/forum?id=HJePno0cYm Transformer-XL: Language Modeling with Longer-Term Dependency \| Z. Dai, Z. Yang, Y. Yang, W.W. Cohen, J. Carbonell, Quoc V. Le, ad R. Salakhutdinov]