LLMS

→ View original post on X — @thom_wolf

Using LLMs to Annotate and Improve Training Data Quality

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@thom_wolf

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21 June 2023 9h03

This is really really cool! I totally buy the idea of using your current LLM to annotate your full training data and increase the quality of subsequent pretrainings. Training data is the most valuable asset, gives back 1000x the care and love you give it!

MotionGPT: Finetuned LLMs for General-Purpose Motion Generation

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21 June 2023 7h17

MotionGPT: Finetuned LLMs are General-Purpose Motion Generators

paper page: https://t.co/FJM2YqZwHR

Generating realistic human motion from given action descriptions has experienced significant advancements because of the emerging requirement of digital humans. While recent… pic.twitter.com/DgUkKy7T7r
— AK (@_akhaliq) 21 juin 2023

MotionGPT: Finetuned LLMs are General-Purpose Motion Generators paper page: https://
huggingface.co/papers/2306.10
900
… Generating realistic human motion from given action descriptions has experienced significant advancements because of the emerging requirement of digital humans. While recent

→ View original post on X — @yuhelenyu

Types of Cognitive AI Encountered in Real Life

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@yuhelenyu

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21 June 2023 6h51

How many types of cognitive #AI have you encountered IRL? https://
aimunch.com/what-is-cognit
ive-ai/
… #AI #ArtificialIntelligence #DataScience #GenerativeAI #WomenInSTEM #NLP #developers #technology #ChatGPT

Phi-1: Efficient 1.3B Parameter Language Model for Code

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21 June 2023 5h33

Textbooks Are All You Need paper page: https://
huggingface.co/papers/2306.11
644
… introduce phi-1, a new large language model for code, with significantly smaller size than competing models: phi-1 is a Transformer-based model with 1.3B parameters, trained for 4 days on 8 A100s, using a selection

→ View original post on X — @mattlynley

Open Source Language Models Race Gains Expert Attention

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@mattlynley

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21 June 2023 5h26

Well there we go. I’d heard it was at least 4 experts but more mechanics on how it works out here. (Prev reported on it last week: https://
supervised.news/p/the-race-for
-open-source-language
…)

RepoFusion: Training Code Models to Understand Repository Context

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21 June 2023 5h05

RepoFusion: Training Code Models to Understand Your Repository paper page: https://
huggingface.co/papers/2306.10
998
… Despite the huge success of Large Language Models (LLMs) in coding assistants like GitHub Copilot, these models struggle to understand the context present in the repository (e.g.,

Guiding Code Language Models with Global Context Using Monitors

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21 June 2023 4h36

Guiding Language Models of Code with Global Context using Monitors paper page: https://
huggingface.co/papers/2306.10
763
… Language models of code (LMs) work well when the surrounding code in the vicinity of generation provides sufficient context. This is not true when it becomes necessary to use

GLIMMER: Generalized Late-Interaction Memory Reranker for Language Models

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21 June 2023 4h10

GLIMMER: generalized late-interaction memory reranker paper page: https://
huggingface.co/papers/2306.10
231
… Memory-augmentation is a powerful approach for efficiently incorporating external information into language models, but leads to reduced performance relative to retrieving text. Recent