Lightning-AI/lit-parrot: Implementation of Falcon, StableLM, Pythia, INCITE language models based on nanoGPT. Supports flash attention, LLaMA-Adapter fine-tuning, pre-training. Apache 2.0-licensed. https://
bit.ly/3pceEd9
#AI #MachineLearning #DeepLearning #LLMs #DataScience
LLMS
-
Lightning-AI lit-parrot: Open-Source Language Model Implementation Framework
By
–
-
10 Essential Things to Know About LLMs and Fine-tuning
By
–
From #finetuning to the latest open-source #LLM models – 10 things you need to know about #LLMs. Join our upcoming episode of #ML Real Talk to get all of your questions answered. https://
my.demio.com/ref/on74p73dZ7
uUP73o?utm_source=twitter
… -
RISE: Retrieval-Based LLM Text Summarization Evaluation Method
By
–
LLMs have shown great results in generating text summarization, but evaluation of the generation quality remains challenging. Drop by the #ACL2023 Google booth at 10:30 am today to learn about RISE, a retrieval-based method that can do evaluation without gold reference.
-
LLM learns patterns from training data representation
By
–
Yeah exactly, I think that’s where the LLM gets this from (ie this pattern being represented in the training data)
-
War of Intelligences in ChatGPT Era Book Review
By
–
Mes followers qui ont eu la gentillesse de lire mon nouveau bouquin « La guerre des intelligences à l’heure de #ChatGPT » peuvent-ils me dire ce qu’ils en ont pensé ?
-
Google unveils Gemini amid AI disorganization
By
–
Google has announced a new AI model from DeepMind: Gemini. Yet another model, yet another name to compete with 'ChatGPT' after LaMDA, Bard, and others… All of this is just proof of the complete disorganization within Google’s AI efforts. 150 teams working on it.
-
Vector Databases Power for Large Language Models
By
–
Discover the power of vector databases for Large Language Models! Vector databases can find visually similar images, comparable documents, and enhance your data analysis capabilities with ease. Read more to explore the world of vector databases: https://
rb.gy/t9p6e -
Gradient Descent as Optimal In-Context Learner in Linear Self-Attention
By
–
One Step of Gradient Descent is Provably the Optimal In-Context Learner with One Layer of Linear Self-Attention paper page: https://
huggingface.co/papers/2307.03
576
… Recent works have empirically analyzed in-context learning and shown that transformers trained on synthetic linear regression -
Self-Instruct: Early Stopping for Minimal Instruction Tuning
By
–
Becoming self-instruct: introducing early stopping criteria for minimal instruct tuning paper page: https://
huggingface.co/papers/2307.03
692
… introduce the Instruction Following Score (IFS), a metric that detects language models' ability to follow instructions. The metric has a dual purpose. -
GPT4RoI: Instruction Tuning LLM on Region-of-Interest
By
–
GPT4RoI: Instruction Tuning Large Language Model on Region-of-Interest paper page: https://
huggingface.co/papers/2307.03
601
… Instruction tuning large language model (LLM) on image-text pairs has achieved unprecedented vision-language multimodal abilities. However, their vision-language