PASD isn’t recent, but still delivers strong results — worth restoring rather than replacing.
Getting it to run again wasn’t a simple dependency issue. It relied on parts of diffusers that no longer exist, while moving to Gradio 6 forced a much newer HF stack — and I couldn’t modify the original source directly.
Recreating the old environment wasn’t practical. So I patched the downloaded code at runtime before import and made it compatible with today’s stack.
That ended up being the only approach that held without forking or freezing everything to outdated versions.
If you’ve used it before (or are curious), feel free to give it another try.
Avatars are everywhere, but here is the reality behind full-system marketing automation. 🚀 Many see "Madame AI" simply as an AI news presenter. She is far deeper than that. Madame AI is a Real-time Agentic AI Assistant we developed to orchestrate entire workflows for marketing and professional media. She manages UGC (User-Generated Content), understands marketing system automation intuitively, and handles complex media tasks. We have solved the character consistency and high production cost bottlenecks that traditionally required immense training and time. By precisely orchestrating every computational step behind videos and branded designs, we have fully automated the pipeline and significantly reduced costs. This capability is built on our extensive experience managing large-scale automation projects with complex requirement documentation (PRD). Grabclip is our public portal and the practical result of that journey. It is the interface where "Madame AI" acts as the intelligent engine. We have spent three years building this pipeline with a clear goal: a 100% local, end-to-end solution that operates despite external restrictions. See the live example on YouTube (our fast-paced AI news podcast with Madame AI) and try the automation portal yourself👇 📺 The Playlist: https://www.youtube.com/playlist?list=PLwEbW4bdYBSCVSziFfJYq4zXop_cyHquO 🌐 Our Portal (Grabclip) — The first practical step in our pipeline: https://grabclip.bilsimaging.com/ hashtag#AgenticAI hashtag#VirtualInfluencer hashtag#FutureOfWork hashtag#GenerativeAI hashtag#TunisiaTech hashtag#MarketingAutomation hashtag#100PercentLocal hashtag#OSMedia hashtag#Grabclip hashtag#RealTimeAssistant hashtag#UGC hashtag#ProfessionalMedia hashtag#TunisiaAI
My TIGER app is now fully working again, with fixes and full compatibility with Gradio 6 🚀
It lets you: - 🎙️ Separate multiple speakers from an audio file - 🎬 Extract each speaker directly from a video - 🎧 Split audio into dialog, music, and sound effects (DnR) - 🎥 Apply DnR separation directly on videos
All powered by lightweight TIGER models for fast and efficient speech separation.
I’ve fixed the Space and brought it back to life: - ✅ Working again after being broken for a while - ✅ Updated to Gradio 6 - ✅ Compatible with ZeroGPU - ✅ Output videos now preserve original resolution and FPS
I also added advanced controls so you can experiment more (tracking, seed, motion, sketch).
I am sharing my study material for AI & ML, these books are really a "bible" and gives very strong foundation, I also have given guidance, introduction and my master notes in the dataset repo card! I hope you will find them helpful, if you have any queries, just start a discussion and I am always there to help you out! Ujjwal-Tyagi/ai-ml-foundations-book-collection
We are thrilled to announce the launch of SKT-OMNI-CORPUS-146T-V1, a massive-scale, high-quality dataset designed to power the next generation of Foundation Models (LLMs) from scratch. Developed at SKT AI LABS, this corpus is not just a collection of data; it’s a mission to decentralize high-grade AI training for regional languages and global knowledge.
💎 Key Highlights:
•• Massive Scale: Targeting a multi-terabyte architecture for 146T-level tokenization.
•• Pure Quality: Curated from 500+ Elite Sources
•• Structured for MoE: Perfectly sharded into 3.5GB standardized units (SKT-𝕻 series) for seamless distributed training.
🤝 Open for Collaboration!
We are looking for AI researchers, CUDA engineers, and data scientists to join us in this journey of building Project Surya and the ST-X Series models. Whether it's optimization, custom tokenization, or architecture design—let’s build the future together.
C-Code-Large is a large-scale corpus of C programming language source code comprising more than 4 million code samples stored in .jsonl format. The dataset is designed to support research and development in large language model (LLM) pretraining, static analysis, and software engineering automation for the C ecosystem.
By offering a high-volume, language-focused dataset, C-Code-Large enables targeted experimentation in low-level programming, memory-constrained environments, and performance-critical systems, where C continues to be a dominant language.
C-Code-Large addresses the lack of large, curated, C-specific datasets, making it possible to conduct focused research on procedural programming paradigms, manual memory management, and system-level abstractions.
We should really have a release date range slider on the /models page. Tired of "trending/most downloaded" being the best way to sort and still seeing models from 2023 on the first page just because they're embedded in enterprise pipelines and get downloaded repeatedly. "Recently Created/Recently Updated" don't solve the discovery problem considering the amount of noise to sift through.
Slight caveat: Trending actually does have some recency bias, but it's not strong/precise enough.
I improved the public demo for TADA — a generative framework for speech modeling via text–acoustic dual alignment.
TADA models speech as a joint sequence of text tokens and acoustic tokens, using a transformer backbone to keep text and audio synchronized during generation.
The original demo already exposed these mechanisms, but the workflow made the pipeline hard to understand.
This updated demo makes the process clearer:
• load the model • prepare a reference voice (optionally with transcript or Whisper auto-transcription) • generate speech conditioned on that reference
It also adds multilingual support.
Presets are included for a few languages, but the model supports more:
Cpp-Code-Large is a large-scale corpus of C++ source code comprising more than 5 million lines of C++ code. The dataset is designed to support research in large language model (LLM) pretraining, code intelligence, software engineering automation, and static program analysis for the C++ ecosystem.
By providing a high-volume, language-specific corpus, Cpp-Code-Large enables systematic experimentation in C++-focused model training, domain adaptation, and downstream code understanding tasks.
Cpp-Code-Large addresses the need for a dedicated C++-only dataset at substantial scale, enabling focused research across systems programming, performance-critical applications, embedded systems, game engines, and large-scale native software projects.
Python-Code-Large is a large-scale corpus of Python source code comprising more than 2 million rows of Python code. The dataset is designed to support research in large language model (LLM) pretraining, code intelligence, software engineering automation, and program analysis for the Python ecosystem.
By providing a high-volume, language-specific corpus, Python-Code-Large enables systematic experimentation in Python-focused model training, domain adaptation, and downstream code understanding tasks.
Python-Code-Large addresses the need for a dedicated Python-only dataset at substantial scale, enabling focused research across data science, backend systems, automation, scientific computing, and AI-driven Python environments.
Public reports allege that Anthropic gobbled up trillions of tokens of copyrighted material and public data to build their castle. 🏰📄 Now that they're sitting on top, they're begging for special laws to protect their profits while pulling the ladder up behind them. 🪜🚫
But the hypocrisy meter just broke! 📉 They are accusing Chinese labs like DeepSeek, Minimax, and Kimi of "huge distillation attacks. The Reality is that You can't just loot the entire internet's library, lock the door, and then sue everyone else for reading through the window. Stop trying to gatekeep the tech you didn't own in the first place. Read the complete article on it: https://huggingface.co/blog/Ujjwal-Tyagi/the-dark-underbelly-of-anthropic
PHP-Code-Large is a large-scale corpus of PHP source code comprising more than 12 million lines of PHP code. The dataset is designed to support research in large language model (LLM) pretraining, code intelligence, software engineering automation, and static program analysis for the PHP ecosystem.
By providing a high-volume, language-specific corpus, PHP-Code-Large enables systematic experimentation in PHP-focused model training, domain adaptation, and downstream code understanding tasks.
PHP-Code-Large addresses the need for a dedicated PHP-only dataset at substantial scale, enabling focused research across backend systems, CMS platforms, APIs, and full-stack PHP environments.
JavaScript-Code-Large is a large-scale corpus of JavaScript source code comprising around 5 million JavaScript files. The dataset is designed to support research in large language model (LLM) pretraining, code intelligence, software engineering automation, and program analysis for the JavaScript ecosystem.
By providing a high-volume, language-specific corpus, JavaScript-Code-Large enables systematic experimentation in JavaScript-focused model training, domain adaptation, and downstream code understanding tasks.
JavaScript-Code-Large addresses the need for a dedicated JavaScript-only dataset at substantial scale, enabling focused research across frontend, backend, and full-stack JavaScript environments. .
