Our results match those on most variables, so my statement holds. Our latest results show that deterministic forecasts are not the only metrics to look, but probablistic ensembles are important. More to follow.
MACHINE LEARNING
-
Comparing SDXL Refiner Model Handoff Timing Across Schedulers
By
–
And compare when to hand off to the SDXL refiner model for different schedulers pic.twitter.com/DruFYqnPlB
— Replicate (@replicate) 28 juillet 2023And compare when to hand off to the SDXL refiner model for different schedulers
-
Explore Different Steps, Schedulers and Guidance Scales
By
–
Try out different steps, schedulers and guidance scales pic.twitter.com/mp6Gb1GcAt
— Replicate (@replicate) 28 juillet 2023Try out different steps, schedulers and guidance scales
-
Lit-GPT: Unified Codebase for Decoder Analysis and Comparison
By
–
It’s kind of hard to analyze across repos due to implementation differences and details along the data loading and finetuning pipelines. That’s where I’d say Lit-GPT is useful because it makes the set of relevant decoders available in the same unified code base
-
Model Documentation Gaps and Empirical Analysis Importance
By
–
Not that I am aware of. On top of that several models don’t even have thorough papers themselves because people are currently rushing them out. I guess the best way is really some empirical analysis coupled with some knowledge bits like falcon and llama2 use multiquery attention
-
Mastering LLM Basics as Foundation for Innovation
By
–
I don't disagree, but I think that in order to innovate it can also be helpful to have the basics down. I.e., implementing and running state-of-the-art LLMs is kind of part of the baseline exercise before going further from there.
-
NeurIPS LLM Efficiency Challenge: Train Model in One Day
By
–
Trying to develop the next huge LLM is fun, but how about a side project with a more reasonable scope like the 1 LLM + 1 GPU + 1 Day NeurIPS efficiency challenge: https://
llm-efficiency-challenge.github.io Below a list of the approved models (PS: Lit-GPT was chosen as the official starter kit ) -
India’s AI Models and Machine Learning Development Initiative
By
–
@jeevprabnivash @DrakeBell @iZotopeInc @Meta @pictoryai @_DigitalIndia @GoI_MeitY @NeGD_GoI @nasscom #ai #aimodels #MachineLearning #INDIAai
-
Eight AI Models Transforming Film Industry Creativity
By
–
AI is transforming the film industry! From AI avatars to text-to-speech videos, AI and ML are proving to be powerful instruments for filmmakers. Check out these eight AI models that are helping unleash creativity in the film industry:
-
LLaMA-like Model Pretraining Accelerated 38% Open-Source
By
–
65-Billion-Parameter Large Model Pretraining Accelerated by 38%, Best Practices for Building LLaMA-like Base Models Open-Source | https://
syncedreview.com/2023/07/18/65-
billion-parameter-large-model-pretraining-accelerated-by-38-best-practices-for-building-llama-like-base-models-open-source/
…
#AI #ML #ArtificialIntelligence #MachineLearning #DeepNeuralNetwork