data-is-better-together-contributor (Data Is Better Together Contributor)

posted an update about 7 hours ago

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259

QIE-2509-Object-Remover-Bbox-v3 is a more stable version of the Qwen Image Edit visual grounding–based object removal model. The app was previously featured in HF Spaces of the Week and is now updated with the latest Bbox-v3 LoRA adapter.

🤗 Demo: prithivMLmods/QIE-Object-Remover-Bbox
🤗 LoRA: prithivMLmods/QIE-2509-Object-Remover-Bbox-v3
🤗 Collection: https://huggingface.co/collections/prithivMLmods/qwen-image-edit-layout-bbox

To learn more, visit the app page or the respective model pages.

1 reply

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sdiazlor

posted an update 4 days ago

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2555

More OSS than ever with the latest pruna 0.3.2 release. It extends existing algorithm families, such as compilers, kernels, and pruners, and adds new ones, including decoders, distillers, enhancers, and recoverers. But it's not only a collection of algorithms; instead, you can easily combine them to get the biggest efficiency win.

Read the full blog here: https://huggingface.co/blog/PrunaAI/pruna-0-3-2-open-source-optimization-algorithms

ZennyKenny

posted an update 4 days ago

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119

One of my New Year's resolutions was to journal more. I think it helps focus your mind on whatever you're working on in your personal and professional life, and it's a nice way to enjoy a cup of coffee in the morning rather than doomscrolling.

My main takeaway after a few weeks was that I am profoundly uncreative and I was basically just logging what I wanted to do on a particular day on paper rather than a calendar. So it was like a less-helpful, analog version of Notion.

Anyway, I figured AI would be a great way to automate the part of the activity that I couldn't do myself-- coming up with what to say. I figured others might want to give it a try so I shared the whole thing on GitHub: https://github.com/kghamilton89/personal-development-journal

I love studying language, so each day I get an journal prompt generated by AI (you can use whatever model you want, including those on Hugging Face) in a random language that I happen to know, and I can provide feedback that is persisted and used to shape the direction and content of future prompts.

Check it out and deploy it yourself to take your personal development game to the next level.

prithivMLmods

posted an update 8 days ago

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4935

The Qwen3.5 Multimodal Understanding Demo, powered by Qwen3.5-2B, is now available on HF Spaces! It is a lightweight model designed for fast image and video reasoning. Built with Gradio, the demo showcases Image QA, Video QA, object detection, and 2D point tracking, along with real-time token streaming.

🤗 Demo: prithivMLmods/Qwen-3.5-HF-Demo
✅ Collection: https://huggingface.co/collections/prithivMLmods/multimodal-implementations
🔗 Qwen3.5-2B: Qwen/Qwen3.5-2B

To learn more, visit the app page or the respective model pages.

alvarobartt

posted an update 9 days ago

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3238

Learn how to deploy Microsoft Research VibeVoice ASR on Microsoft Azure Foundry with Hugging Face to generate rich audio transcriptions with Who, When, and What! 💥

> 🕒 60-minute single-pass processing, no chunking or stitching
> 👤 Customized hotwords to guide recognition on domain-specific content
> 📝 Rich transcription: joint ASR + diarization + timestamping in one pass
> 🌍 50+ languages with automatic detection and code-switching support
> 🤗 Deployed on Microsoft Foundry via an OpenAI-compatible Chat Completions API

https://huggingface.co/docs/microsoft-azure/foundry/examples/deploy-vibevoice-asr

ajibawa-2023

posted an update 10 days ago

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3711

Cpp-Code-Large
Dataset: ajibawa-2023/Cpp-Code-Large

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.

3 replies

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Goekdeniz-Guelmez

submitted a paper to Daily Papers 10 days ago

DynaMoE: Dynamic Token-Level Expert Activation with Layer-Wise Adaptive Capacity for Mixture-of-Experts Neural Networks

Paper • 2603.01697 • Published 13 days ago • 2

Goekdeniz-Guelmez

authored a paper 12 days ago

DynaMoE: Dynamic Token-Level Expert Activation with Layer-Wise Adaptive Capacity for Mixture-of-Experts Neural Networks

Paper • 2603.01697 • Published 13 days ago • 2

prithivMLmods

posted an update 12 days ago

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3961

QIE-Object-Remover-Bbox Demo removes objects and artifacts from selected regions using bounding box grounding. Built on Qwen-Image-Edit-2509 with Rapid Diffusers acceleration, it delivers fast 4-step inference via the QIE-2509 adapter. 🤗🔥

🔗Demo Space: prithivMLmods/QIE-Object-Remover-Bbox
🔗Qwen-Image-Edit-Rapid-AIO: prithivMLmods/Qwen-Image-Edit-Rapid-AIO-V4
🔗Adapter-(LoRA): prithivMLmods/QIE-2509-Object-Remover-Bbox

🔗Collection: https://huggingface.co/collections/prithivMLmods/qwen-image-edit-layout-bbox

To learn more, visit the app page or the respective model pages.

1 reply

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ajibawa-2023

posted an update 15 days ago

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3470

Python-Code-Large
Dataset: ajibawa-2023/Python-Code-Large

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.

1 reply

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prithivMLmods

posted an update 18 days ago

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FireRed-Image-Edit-1.0 (Rapid) Fast Experimental Demo is Out! 🚀🤗

Demo: prithivMLmods/FireRed-Image-Edit-1.0-Fast

-> Paired the EditPlusPipeline with the Diffusers-compatible transformer weights of Rapid AIO from Qwen-Image-Edit. (experimental)
-> This fusion delivers more accurate instruction following, higher image quality, and consistent visual coherence @ 4-step fast inference.
-> Better maintains text styles with high fidelity, along with high-quality old photo restoration, enhancement, and best-in-class virtual try-on.

ajibawa-2023

posted an update 19 days ago

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2568

PHP-Code-Large

Dataset: ajibawa-2023/PHP-Code-Large

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.

prithivMLmods

posted an update 22 days ago

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3216

Try the demo for Qwen3-VL-abliterated-MAX-Fast: prithivMLmods/Qwen3-VL-abliterated-MAX-Fast (Unredacted: Ask Anything with Near-Zero Refusal Rates). The full model series collection is available here: https://huggingface.co/collections/prithivMLmods/unredacted-max-vl

mariagrandury

authored 2 papers 23 days ago

BabyBabelLM: A Multilingual Benchmark of Developmentally Plausible Training Data

Paper • 2510.10159 • Published Oct 11, 2025 • 3

Measuring what Matters: Construct Validity in Large Language Model Benchmarks

Paper • 2511.04703 • Published Nov 3, 2025 • 8

ajibawa-2023

posted an update 24 days ago

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3251

JavaScript-Code-Large
ajibawa-2023/JavaScript-Code-Large

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. .

ZennyKenny

posted an update 25 days ago

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851

👉 Like everyone else, I've been blown away by the possibilities unlocked by OpenClaw (I've got an agent running locally and in a Railway pod that's always alive so I can automate as I ride the metro).

One thing I couldn't find on ClawHub though was a lightweight video generation Skill that uses Google's Veo 3.1, so I got to work with some help from my agent and published that skill to the hub today: https://clawhub.ai/kghamilton89/veo-video-generator

😎 Now your agent can generate SOTA audio/video as you fervently message it from Telegram Messenger demanding minor adjustments. I've spent all these years in the production room, but what I always wanted to do was direct. Feels good man.

ajibawa-2023

posted an update 26 days ago

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3132

Java-Code-Large ( ajibawa-2023/Java-Code-Large)

Java-Code-Large is a large-scale corpus of publicly available Java source code comprising more than 15 million java codes. The dataset is designed to support research in large language model (LLM) pretraining, code intelligence, software engineering automation, and program analysis.

By providing a high-volume, language-specific corpus, Java-Code-Large enables systematic experimentation in Java-focused model training, domain adaptation, and downstream code understanding tasks.