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Papers Explained 56: Alpaca
Papers Explained 56: Alpaca
Alpaca is fine-tuned from Meta’s LLaMA 7B model. The Alpaca model is trained on 52K instruction-following demonstrations generated in the…
Ritvik Rastogi
Sep 17
Papers Explained 55: LLaMA
Papers Explained 55: LLaMA
LLaMA is a collection of foundation language models ranging from 7B to 65B parameters, trained on trillions of tokens using publicly…
Ritvik Rastogi
Sep 10
Papers Explained 54: ChatGPT
Papers Explained 54: ChatGPT
ChatGPT is an interactive model designed to engage in conversations. Its conversational format allows ChatGPT to respond to subsequent…
Ritvik Rastogi
Sep 3
Papers Explained 53: Galactica
Papers Explained 53: Galactica
Galactica is an LLM specializing in scientific knowledge, surpasses existing models on a variety of scientific tasks, excelling in…
Ritvik Rastogi
Aug 28
Papers Explained 52: BLOOM
Papers Explained 52: BLOOM
BLOOM is a 176B-parameter open-access decoder-only transformer model, collaboratively developed by hundreds of researchers, aiming to…
Ritvik Rastogi
Aug 19
Papers Explained 51: OPT
Papers Explained 51: OPT
Open Pre-trained Transformers (OPT) comprise a suite of decoder-only pre-trained transformers with parameter ranges from 125M to 175B…
Ritvik Rastogi
Aug 13
Papers Explained 50: PaLM
Papers Explained 50: PaLM
Pathways Language Model (PaLM) is a 540-billion parameter, densely activated, Transformer language model. It is trained on 6144 TPU v4…
Ritvik Rastogi
Aug 6
Papers Explained 49: Chinchilla
Papers Explained 49: Chinchilla
This paper investigated the optimal model size and number of tokens for training a transformer LLM within a given compute budget and…
Ritvik Rastogi
Jul 30
Papers Explained 48: InstructGPT
Papers Explained 48: InstructGPT
This paper shows an avenue for aligning language models with user intent on a wide range of tasks by fine-tuning with human feedback…
Ritvik Rastogi
Jul 23
Most Popular
Detecting Sarcasm with Deep Convolutional Neural Networks
Detecting Sarcasm with Deep Convolutional Neural Networks
Overview This paper addresses a key NLP problem known as sarcasm detection using a combination of models based on convolutional neural…
elvis
Apr 30, 2018
A Light Introduction to Transfer Learning for NLP
A Light Introduction to Transfer Learning for NLP
In this post, I will introduce transfer learning for natural language processing and key questions necessary to better understand this…
elvis
Jul 26, 2018
Deep Learning for NLP: An Overview of Recent Trends
Deep Learning for NLP: An Overview of Recent Trends
In a timely new paper, Young and colleagues discuss some of the recent trends in deep learning based natural language processing (NLP)…
elvis
Aug 23, 2018
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