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Undress AI Pro is a controversial computer vision application that uses machine learning to remove clothing from images of people. It was based on deep learning and generative adversarial networks (GANs). The technology powering Undress AI and DeepNude was based on deep learning and generative adversarial networks (GANs). GANs involve two neural networks competing against each other - a generator creates synthetic images trying to mimic the training data, while a discriminator tries to distinguish the real images from the generated ones. Through this adversarial process, the generator learns to produce increasingly realistic outputs. For Undress AI, the GAN was trained on a dataset of nude and clothed images, allowing it to "unclothe" people in new images by generating the nudity.

llm-swarm is a tool designed to manage scalable open LLM inference endpoints in Slurm clusters. It allows users to generate synthetic datasets for pretraining or fine-tuning using local LLMs or Inference Endpoints on the Hugging Face Hub. The tool integrates with huggingface/text-generation-inference and vLLM to generate text at scale. It manages inference endpoint lifetime by automatically spinning up instances via `sbatch`, checking if they are created or connected, performing the generation job, and auto-terminating the inference endpoints to prevent idling. Additionally, it provides load balancing between multiple endpoints using a simple nginx docker for scalability. Users can create slurm files based on default configurations and inspect logs for further analysis. For users without a Slurm cluster, hosted inference endpoints are available for testing with usage limits based on registration status.