Nope. Not yet. I'm not sure if there's even a regional prompting technique in diffusers world.
PROMPT ENGINEERING
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SDXL Refiner Settings and Configuration Guide
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Yep, using the SDXL refiner – here are all the settings: https://
replicate.com/p/7xhk3rtbknhl
kask5xxjmme2ou
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Regional Prompting Technique: Advanced Applications and Refinements
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I need to revisit this technique. I think there’s a lot more that can be done now with regional prompting. https://t.co/Du5PlnlajY
— fofr (@fofrAI) 3 novembre 2023I need to revisit this technique. I think there’s a lot more that can be done now with regional prompting.
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What prompt generated this gorgeous AI artwork?
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This is a gorgeous piece! What did you use as a prompt?
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Understanding Context Window in Large Language Models
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One of the most important concepts to understand in the age of large language models is the “context window”. Every output is dictated by what’s in the context window, here’s a great write up on it:
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Chain of Density: Advanced GPT-4 Summarization Technique
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From Sparse to Dense: GPT-4 Summarization with Chain of Density Prompting https://
arxiv.org/abs/2309.04269 @GriffinAdams92 Alexander Fabbri @faisalladhak @lehmer16 @noemieelhadad -
DALL-E 3 and Fine-tuning Capabilities Comparison
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Yeah, Dalle3 is amazing too, it’s different use-cases too, /tune feels a lot like a “simplified” fine-tuning.
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Adaptive Prompting Approach Improves LLM Few-Shot Performance
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Introducing a new approach for adaptive prompting of #LLMs that train with unlabeled samples + pseudo-demonstrations generated by the model itself to close the gap between few-shot and 0-shot performance on reasoning, NLU and language generation tasks. → https://t.co/ZtSEZOxNCc pic.twitter.com/5H7YE0usc3
— Google AI (@GoogleAI) 2 novembre 2023Introducing a new approach for adaptive prompting of #LLMs that train with unlabeled samples + pseudo-demonstrations generated by the model itself to close the gap between few-shot and 0-shot performance on reasoning, NLU and language generation tasks. → https://
goo.gle/3tY00IB -
GPT Monitoring: Token Optimization and Prompt Quality Strategies
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Efficient GPT-based products require effective monitoring strategies. Keys to success: optimal token usage, constant prompt quality improvement, and averting user-facing disasters. Developers, remember these tips!
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Master Prompt Engineering and LLM Interactions in November Webinar
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Uncover #GenAI magic on Nov 28 in our webinar. Dive into prompt crafting, streamline LLM interactions, and more. Don't miss out on leveling up your Prompt Engineering skills. Register now! https://
domino.buzz/3Skg0yN #Webinar #AI