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The stuff: https://github.com/Stability-AI/sd3.5#stable-diffusion-35 Also relevant: https://github.com/huggingface/blog/blob/main/sd3-5.md

This post is misleading, in a way that is hard to do accidentally. - They compare the performance of this model to the worst 7B code llama model. The base code llama 7B python model scores 38.4% on humaneval, versus the non-python model, which only scores 33%. - They compare their instruct tuned model to non-instruct-tuned models. Instruction tuning can add 20% or more to humaneval performance. For example, WizardLM 7B scores 55% on humaneval [1], and I've trained a 7B model that scores 62% [2]. - For another example of instruction tuning, Stablecode instruct tuned benchmarks at 26%, not the 20% they cite for the base model [3] - Starcoder, when prompted properly, scores 40% on humaneval [4] - They do not report their base model performance (as far as I can tell) This is interesting work, and a good contribution, but it's im

If you just want to do inference/mess around with the model and have a 16GB GPU, then this[0] is enough to paste into a notebook. You need to have access to the HF models though. 0. https://github.com/huggingface/blog/blob/main/llama2.md#usin...