Still looking for best practices on #LoRA adapters config for efficient #LLM fine-tuning. Especially on Llama models. Any insight to share about it?
https://t.co/XQGfdusWzs
#HuggingFace#Transformers#NLProc
@PTownAllStar93@fchollet I think there is a major issue you are not considering here: making a model strongly specialized in several distinct domains is hard. Think about catastrophic forgetting. For now we can only hypothesize that AGI 1st training phase would mitigate it.
Python has become the most popular language on GitHub. I only wish for two more things: that browsers start supporting Python as a frontend language and that Excel fully supports it as a macro language. The world will be a better place.
A fundamental question to ask for AI agent research: what is the major bottleneck that cannot be addressed by simply scaling up data and training next version of MLLMs?
BREAKING NEWS
The Royal Swedish Academy of Sciences has decided to award the 2024 #NobelPrize in Literature to the Attention Is All You Need authors.
Their work has made thousands cry, laugh, or rich and made GPUs go brrr
@SpectrGen Thanks for your post, I was tired of reading all these posts saying RAG is wonderful! You're completely right + RAG setup is not suitable for multiple sources of info / coreferences / meta info about the data
Ravie d’avoir pu prendre la parole en session commune de #jeptaln2024 hier pour parler de détection d’émotions en conversation #ERC 😁 Lire l’article : https://t.co/UnvPVgJ0u9
@iamgingertrash@ylecun@alex_peys By saying « optimal answer », you assume that it exists and that we can evaluate the distance to optimality for any answer provided by the LLM. These are very strong assumptions to be fair…