All tags
Model: "stable-diffusion-1.5"
Music's Dall-E moment
griffin command-r-plus gpt-4-0613 gpt-4-0314 mistral-8x22b codegemma stable-diffusion-1.5 command-r gemini-1.5 google mistral-ai lmsys cohere model-architecture benchmarking open-source model-quantization memory-optimization inference-speed multimodality finetuning performance-optimization audio-processing andrej-karpathy
Google's Griffin architecture outperforms transformers with faster inference and lower memory usage on long contexts. Command R+ climbs to 6th place on the LMSYS Chatbot Arena leaderboard, surpassing GPT-4-0613 and GPT-4-0314. Mistral AI releases an open-source 8x22B model with a 64K context window and around 130B total parameters. Google open-sources CodeGemma models with pre-quantized 4-bit versions for faster downloads. Ella weights enhance Stable Diffusion 1.5 with LLM for semantic alignment. Unsloth enables 4x larger context windows and 80% memory reduction for finetuning. Andrej Karpathy releases LLMs implemented in pure C for potential performance gains. Command R+ runs in realtime on M2 Max MacBook using iMat q1 quantization. Cohere's Command R model offers low API costs and strong leaderboard performance. Gemini 1.5 impresses with audio capabilities recognizing speech tone and speaker identification from audio clips.
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.
AdamW -> AaronD?
claude-3-opus llama-3 llama-3-300m bert-large stable-diffusion-1.5 wdxl openai hugging-face optimizer machine-learning-benchmarks vision time-series-forecasting image-generation prompt-injection policy-enforcement aaron-defazio
Aaron Defazio is gaining attention for proposing a potential tuning-free replacement of the long-standing Adam optimizer, showing promising experimental results across classic machine learning benchmarks like ImageNet ResNet-50 and CIFAR-10/100. On Reddit, Claude 3 Opus has surpassed all OpenAI models on the LMSys leaderboard, while a user pretrained a LLaMA-based 300M model outperforming bert-large on language modeling tasks with a modest budget. The new MambaMixer architecture demonstrates promising results in vision and time series forecasting. In image generation, Stable Diffusion 1.5 with LoRAs achieves realistic outputs, and the WDXL release showcases impressive capabilities. AI applications include an AI-generated Nike spec ad and a chatbot built with OpenAI models that may resist prompt injections. OpenAI is reportedly planning a ban wave targeting policy violators and jailbreak users. "The high alpha seems to come from Aaron Defazio," highlighting his impactful work in optimizer research.