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A central place for all AI creators wanting to use the different AI Tools that provides HuggingFace for their film creations

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iproskurina  authored a paper 9 days ago
Fair-GPTQ: Bias-Aware Quantization for Large Language Models
iproskurina  authored a paper 9 days ago
HatePrototypes: Interpretable and Transferable Representations for Implicit and Explicit Hate Speech Detection
iproskurina  authored a paper 9 days ago
RILEC: Detection and Generation of L1 Russian Interference Errors in English Learner Texts
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Nymbo 
posted an update about 15 hours ago
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I made a skill to autonomously mass download entire music discographies from any platform. You give the agent a long list of artists and send the prompt as a /goal. The agent develops a list of all mainline albums/projects of each artist, manually checks each playlist to verify the tracks beings curated, then downloads it all in efficient batches using yt-dlp.

I added 37,000 new tracks to my local library overnight. Check it out here: https://github.com/Nymbo/Music-Downloader-Skill
Shrijanagain 
posted an update 6 days ago
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We are pleased to announce that the W-IMG Vision Dataset infrastructure is officially live.

The complete asset infrastructure is now accessible on Hugging Face for internal validation and architecture scaling targets.

Dataset Endpoint - sKT-Ai-Labs/W-IMG

#SovereignAI #ComputerVision #MachineLearning #OpenSource
fffiloni 
posted an update 9 days ago
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I built HF Radio on Hugging Face Spaces 📻
fffiloni/HF-Radio

A live community radio for AI-generated songs, powered by tracks created with ACE-Step.

You can tune in, discover community-made songs in many languages, vote on what sounds good, and mark your real favorites as Bangers.

The more people listen, vote, and create, the better the station gets.

Under the hood, it connects a few Hugging Face pieces together:

Spaces for the live app, HF buckets for community tracks, OAuth for signed-in listeners, server-side streaming with ffmpeg, hourly playlist refreshes, moderation, jingles, and community feedback loops.

It’s not just a playlist.

It’s a shared taste experiment:
new songs get a shot every hour, and the community helps decide what deserves another spin.

Come listen.
Find weird gems.
Support the Bangers.
Shape the radio.

—> fffiloni/HF-Radio
iproskurina 
authored 3 papers 9 days ago
fffiloni 
posted an update 14 days ago
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Great technical guide by Nico Martin on the Hugging Face blog, showing how to use Transformers.js inside a Chrome extension and run ONNX models from the Hub locally with WebGPU inside a Manifest V3 extension.

The interesting part: this is not just a chatbot in a side panel.

The article walks through the architecture behind a browser agent that can read open tabs, query webpages, search history, and highlight elements directly on the page — with models downloaded from the Hugging Face Hub, cached under the extension origin, and executed locally instead of being called through a remote API for every prompt.

A strong blueprint for building local-first web copilots, reading assistants, and AI-powered browsing workflows.

Article: https://huggingface.co/blog/transformersjs-chrome-extension
fffiloni 
posted an update 16 days ago
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I’ve been reading “What if AI systems weren’t chatbots?”
What if AI systems weren't chatbots? (2605.07896) 👀

The paper asks a simple but important question: what if the chatbot interface is not just a neutral wrapper around AI models, but part of the problem?

A chatbot can make a system feel more capable, more certain, and more “human” than it really is. That matters, because interfaces shape how we trust, use, and delegate to AI systems.

When everything becomes: ask → answer
we can lose sight of the actual workflow:
- parameters
- alternatives
- uncertainty
- intermediate steps
- failure modes
- human control

For creative AI especially — image, video, editing, animation — I’m not sure “chat” should always be the default interface.

Sometimes we need a conversation.
But often we need a canvas, a timeline, sliders, masks, previews, comparisons, and visible pipelines.

This is also why I find many open ML demos interesting: Spaces, Gradio apps, visual tools, small focused interfaces.

They often explore another direction — not just better assistants, but better tools. 🤗
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ajibawa-2023 
posted an update 21 days ago
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Stitched-Reasoning-Trajectories-7M

Dataset: ajibawa-2023/Stitched-Reasoning-Trajectories-7M
Stitched-Reasoning-Trajectories-7M is a massive-scale, synthetic multi-hop reasoning dataset. It was built by algorithmically "stitching" together discrete reasoning traces from the original glaiveai/reasoning-v1-20m dataset into continuous, coherent, and logically structured multi-agent trajectories.

By extracting internal sub-questions from <think> blocks and mapping high-information keyword overlaps, this dataset transforms single-turn Q&A pairs into deep, multi-step research plans. To ensure high quality and eliminate "topic drift," every trajectory has been verified using a dense semantic embedding model (BAAI/bge-large-en-v1.5).

The resulting dataset consists of 709 .jsonl files containing over 7.2 million entirely deduplicated, highly coherent reasoning chains.
Ujjwal-Tyagi 
posted an update 24 days ago
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6 Open-Source Libraries to FineTune LLMs
1. Unsloth
GitHub: https://github.com/unslothai/unsloth
→ Fastest way to fine-tune LLMs locally
→ Optimized for low VRAM (even laptops)
→ Plug-and-play with Hugging Face models

2. Axolotl
GitHub: https://github.com/OpenAccess-AI-Collective/axolotl
→ Flexible LLM fine-tuning configs
→ Supports LoRA, QLoRA, multi-GPU
→ Great for custom training pipelines

3. TRL (Transformer Reinforcement Learning)
GitHub: https://github.com/huggingface/trl
→ RLHF, DPO, PPO for LLM alignment
→ Built on Hugging Face ecosystem
→ Essential for post-training optimization

4. DeepSpeed
GitHub: https://github.com/microsoft/DeepSpeed
→ Train massive models efficiently
→ Memory + speed optimization
→ Industry standard for scaling

5. LLaMA-Factory
GitHub: https://github.com/hiyouga/LLaMA-Factory
→ All-in-one fine-tuning UI + CLI
→ Supports multiple models (LLaMA, Qwen, etc.)
→ Beginner-friendly + powerful

6. PEFT
GitHub: https://github.com/huggingface/peft
→ Fine-tune with minimal compute
→ LoRA, adapters, prefix tuning
→ Best for cost-efficient training
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Sri-Vigneshwar-DJ 
posted an update 25 days ago
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![Feather DB LongMemEval Results]( Hawky-ai/longmemeval-results)

We ran Feather DB v0.8.0 on LongMemEval (ICLR 2025) — 500 questions across real multi-session conversations, up to 115K tokens each.

**Score: 0.693** · GPT-4o full-context baseline: 0.640
Full 500-question run with Gemini-Flash: **$2.40**

Per-axis breakdown:
→ Info-extraction: **0.942**
→ Knowledge-update: **0.714**
→ Multi-session: **0.606**
→ Temporal: **0.477** ← the hard one, Phase 9 addresses this

Architecture: Hybrid BM25+dense · adaptive temporal decay · embedded (no server) · p50 = 0.19ms · MIT

pip install feather-db

Raw results + audit JSONs: Hawky-ai/longmemeval-results
Ujjwal-Tyagi 
posted an update about 1 month ago
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This is the best set of AI and ML books and a full guide to learning machine learning from the ground up. This is my study material that I used, so I thought it would be helpful to share it with others. Like, share, and add it to your collection at Ujjwal-Tyagi/ai-ml-foundations-book-collection.
fffiloni 
posted an update about 1 month ago
fffiloni 
posted an update about 1 month ago
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🚀 RB-Modulation is back on Hugging Face Spaces!

This is an older project that recently broke due to dependency changes, but it’s now fixed and running again ✅

👉 What’s fixed:
- GroundingDINO & LangSAM installation
- compatibility with recent environments
- GPU inference running smoothly again

👉 Try it here:
fffiloni/RB-Modulation

Feel free to give it a try again — feedback welcome!
Ujjwal-Tyagi 
posted an update about 1 month ago
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We are hiring at Shirova AI. We need AI researchers and engineers to work in our research lab. Shirova AI is a research lab in India, so we can help our researchers move to nearby workspaces or let them work from home without ever coming to the lab. We're building our founding team, so the pay will be good. You can learn, so don't hesitate to mail us at: careers@shirova.com
ajibawa-2023 
posted an update about 1 month ago
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Ruby-Code-Large
Dataset : ajibawa-2023/Ruby-Code-Large

Ruby-Code-Large is a large-scale corpus of Ruby programming language source code comprising 331,743 code samples stored in .jsonl format. The dataset is designed to support research and development in large language model (LLM) pretraining, static analysis, web application development, and software engineering automation within the Ruby ecosystem.

By offering a substantial, language-focused dataset, Ruby-Code-Large enables targeted experimentation in dynamic programming, object-oriented design, and rapid application development—areas where Ruby is widely used, particularly in web frameworks and scripting.

Ruby-Code-Large addresses the lack of large, curated, Ruby-specific datasets, enabling focused research on expressive syntax, metaprogramming, and high-level abstractions.
ajibawa-2023 
posted an update about 1 month ago
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Go-Code-Large
Dataset: ajibawa-2023/Go-Code-Large

Go-Code-Large is a large-scale corpus of Go (Golang) programming language source code, comprising 316,427 code samples stored in .jsonl format. The dataset is designed to support research and development in large language model (LLM) pretraining, static analysis, cloud-native systems, and modern backend software engineering.

By offering a focused and curated dataset for Go, this corpus enables experimentation in concurrent programming, distributed systems, and performance-oriented backend services—domains where Go is widely adopted.

Go-Code-Large addresses the relative scarcity of large, language-specific datasets for Go, enabling targeted research into idiomatic Go patterns, concurrency primitives, and scalable system design.
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boroll2347 
posted an update about 1 month ago
fffiloni 
posted an update about 2 months ago
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✨ PASD Magnify is back on Hugging Face Spaces

fffiloni/PASD

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.
Bils 
posted an update about 2 months ago
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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