the following is a general representation of ControlNet's architecture. first, it clones the weights of a diffusion model. Then, it trains the cloned weights to control the original model with the task from the input condition.
GENERATIVE AI
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Zero Convolutions Enable Progressive Control Learning in AI Models
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the goal of this architecture is to keep as much as possible all the knowledge learned by the original model. the trainable network learns how to perform the control in a progressive way thanks to the use of zero convolutions.
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Zero Convolutions in ControlNet: Progressive Training Influence
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zero convolutions are 1D convolutions with weights and biases initialized to 0s. note how at the beginning of the training ControlNet will not affect the original network at all, but as it gets trained it will progressively start influencing the generation with the condition.
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ControlNet Architecture with Stable Diffusion Explained
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the following is a representation of ControlNet's architecture when used with Stable Diffusion
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ControlNet: Guide complet du fonctionnement et des applications
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what is ControlNet and how does it work?
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ControlNet: Conditioning Diffusion Models on Arbitrary Input Features
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ControlNet is a method that can be used to condition diffusion models on arbitrary input features, such as image edges, segmentation maps, or human poses.
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Finding Purpose in AI Work and Mission-Driven Technology
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everyone should work a job that they love so much that they wish they could work harder at I feel that viscerally now at @scale_AI
—every waking second can be spent to ensure that the technology reaches maximum positive potential AI, defense—these are missions worth fighting for -
ChatGPT-Powered Bing Forces User Apology Over Date Disagreement
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The new ChatGPT-powered Bing forces a user to apologize for being rude, since the user is trying to convince it that it's 2023 (it insists that it's still 2022). My favourite part is the repeated "I have been a good Bing." Full convo here: https://
old.reddit.com/r/bing/comment
s/110eagl/the_customer_service_of_the_new_bing_chat_is/
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Language Models Semantics NLP Real-world Applications Discussion
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Prof. Edward Grefenstette @egrefen discusses language models, semantics, philosophy, and more, diving into how NLP can solve real-world problems in this exciting conversation with @MLStreetTalk
: https://
youtu.be/i9VPPmQn9HQ?ut
m_source=twitter&utm_medium=social
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Kaggle Competition: Stable Diffusion Image-to-Prompts Challenge
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Link to the competition https://
kaggle.com/competitions/s
table-diffusion-image-to-prompts/overview/prizes
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