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Topic: "character-lora-training"
Anime pfp anon eclipses $10k A::B prompting challenge
command-r-plus-104b stable-diffusion-1.5 openai ollama huggingface quantization model-optimization streaming prompt-engineering self-prompting image-composition character-lora-training model-size open-source-licenses memes humor victor-taelin futuristfrog
Victor Taelin issued a $10k challenge to GPT models, initially achieving only 10% success with state-of-the-art models, but community efforts surpassed 90% success within 48 hours, highlighting GPT capabilities and common skill gaps. In Reddit AI communities, Command R Plus (104B) is running quantized on M2 Max hardware via Ollama and llama.cpp forks, with GGUF quantizations released on Huggingface. Streaming text-to-video generation is now available through the st2v GitHub repo. WD Tagger v3 was released for mass auto-captioning datasets with a WebUI. Lesser-known prompting techniques like self-tagging and generational frameworks produced thought-provoking outputs in OpenAI discussions, including experiments with self-evolving system prompts. Stable Diffusion users discussed image composition importance for training character LoRAs and best checkpoints for video game character generation. Discussions also covered scarcity of 5B parameter models and open(ish) licenses for open source AI. Memes included jokes about ChatGPT and Gemini training data differences.