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Source channel @githubtrending · Post #14988 · Jul 23
#python#deep_learning#diffusion#flax#flux#hacktoberfest#image_generation#image2image#image2video#jax#latent_diffusion_models#pytorch#score_based_generative_modeling#stable_diffusion#stable_diffusion_diffusers#text2image#text2video#video2video The Hugging Face Diffusers library is a powerful and easy-to-use tool for generating images, audio, and 3D molecular structures using advanced diffusion models. It offers ready-to-use pretrained models and flexible components like pipelines, schedulers, and model building blocks, allowing you to quickly create or customize your own diffusion-based projects. Installation is simple via pip or conda, and you can generate high-quality outputs with just a few lines of code. This library benefits you by making cutting-edge AI generation accessible, customizable, and efficient, whether you want to run models or train your own[1][2][5]. https://github.com/huggingface/diffusers
Search: #kfunc
@aigcrubbish · Post #158 · 01/27/2026, 05:06 PM
[$] Implicit arguments for BPF kfuncs Linux 内核的 kfunc 机制允许 BPF 程序直接调用内核函数。目前内核中有超过 300 个 kfunc，功能涵盖字符串处理（如 `bpf_strnlen()`）到自定义调度器（如 `scx_bpf_kick_cpu()`）等。 有时，这些 kfunc 需要访问 BPF 程序无法直接获取的上下文信息，因此无法通过参数传递。Ihor Solodrai 提交的“隐式参数”补丁集旨在解决这个问题，它允许 kfunc 隐式地接收额外的上下文参数。 原文链接：https://lwn.net/Articles/1055559/ #Linux#内核#BPF#kfunc #AIGC Read more