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https://levelup.gitconnected.com/how-to-successfully-run-a-llm-fine-tuning-project-my-personal-insights-on-choosing-the-right-c3640d00665dhttps://levelup.gitconnected.com/a-step-by-step-guide-to-runing-mistral-7b-ai-on-a-single-gpu-with-google-colab-274a20eb9e40https://levelup.gitconnected.com/unleash-mistral-7b-power-how-to-efficiently-fine-tune-a-llm-on-your-own-data-4e4386a6bbdcWhen should yo..

https://www.slideshare.net/slideshow/roformer-enhanced-transformer-with-rotary-position-embedding/250482951https://medium.com/ai-insights-cobet/rotary-positional-embeddings-a-detailed-look-and-comprehensive-understanding-4ff66a874d83https://www.youtube.com/watch?v=o29P0Kpobz0https://medium.com/@ngiengkianyew/understanding-rotary-positional-encoding-40635a4d078eThe Need for Positional Embeddings ..

https://arxiv.org/pdf/2112.10752AbstractBy decomposing the image formation process into a sequential application of denoising autoencoders, diffusion models (DMs) achieve state-of-the-art synthesis results on image data and beyond. Additionally, their formulation allows for a guiding mechanism to control the image generation process without retraining. However, since these models typically opera..

https://arxiv.org/pdf/2105.05233AbstractWe show that diffusion models can achieve image sample quality superior to the current state-of-the-art generative models. We achieve this on unconditional image synthesis by finding a better architecture through a series of ablations. For conditional image synthesis, we further improve sample quality with classifier guidance: a simple, compute-efficient m..

https://arxiv.org/pdf/2102.09672AbstractDenoising diffusion probabilistic models (DDPM) are a class of generative models which have recently been shown to produce excellent samples. We show that with a few simple modifications, DDPMs can also achieve competitive loglikelihoods while maintaining high sample quality. Additionally, we find that learning variances of the reverse diffusion process al..

https://mlberkeley.substack.com/p/vq-vae?utm_source=publication-searchLike everyone else in the ML community, we’ve been incredibly impressed by the results from OpenAI’s DALL-E. This model is able to generate precise, high quality images from a text description. It can even produce creative renderings of objects that likely don’t exist in the real world, like “an armchair in the shape of an avo..

https://medium.com/@paluchasz/understanding-flamingo-visual-language-models-bea5eeb05268Flamingo is a Visual Language Model, one of the earliest multimodal generative models. This article is a deep dive of what it is, how it works and how it is used.IntroductionFlamingo was introduced in the paper Flamingo: a Visual Language Model for Few-Shot Learning in 2022. It is a multimodal Language Model ..

Google DeepMind https://deepmind.google/discover/blog/tackling-multiple-tasks-with-a-single-visual-language-model/One key aspect of intelligence is the ability to quickly learn how to perform a new task when given a brief instruction. For instance, a child may recognise real animals at the zoo after seeing a few pictures of the animals in a book, despite differences between the two. But for a ty..