@phygitalcreative · Post #3136 · 06/26/2023, 01:04 AM
А вот подвезли официальный код DragGAN. Интересно насколько его работа отличается от неофициальной имплементации. В основе StyleGAN3 и StyleGAN-Human. Код #image2image
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Source channel @githubtrending · Post #15549 · Mar 8
#python#ai_automation#api#audio_overview#claude#cli_tool#flashcards#google_notebooklm#notebooklm#notebooklm_api#notebookln#podcast_generator#python#python_api#quiz_generator#sdk#skills#study_tools notebooklm-py is a free Python tool and CLI for full access to Google NotebookLM's features, like creating notebooks, adding sources (URLs, PDFs, YouTube), chatting, deep research, and generating podcasts, videos, quizzes, slides, mind maps in formats like MP3, MP4, JSON. It offers extras the web lacks, such as batch downloads, editable PPTX, and mind map data. You benefit by automating research, content creation, and exports programmatically for faster prototypes, pipelines, or AI agents—saving time on manual UI work. https://github.com/teng-lin/notebooklm-py
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@phygitalcreative · Post #3136 · 06/26/2023, 01:04 AM
А вот подвезли официальный код DragGAN. Интересно насколько его работа отличается от неофициальной имплементации. В основе StyleGAN3 и StyleGAN-Human. Код #image2image
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@phygitalcreative · Post #3158 · 06/29/2023, 01:26 PM
Mixed Image Editing Playground AI выкатили редактор изображений с большинством последних достижений в этой области. #image2image#imageediting
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@githubtrending · Post #14988 · 07/23/2025, 12:00 AM
#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