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merve 
in blog-explorers/README 4 days ago

Update README.md

#12 opened 4 days ago by
merve
thecollabagepatch 
posted an update about 2 months ago
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415
hey musicians

hf continues to make the anti-suno device possible with gary4juce, the VST for your DAW that doesn't try to replace you.

v2 just released. https://thepatch.gumroad.com/l/gary4juce (pay what you want)

now you can use google's magenta-realtime model to generate 48k samples based on your input audio (or other model outputs...there's 4 to play with now).

just duplicate my hf space, turn on an L4/L40s and throw the url into the plugin.

i've got a few finetunes you can switch to as well. or you can push your finetune to the hub and play around.

the space: thecollabagepatch/magenta-retry (you can also use the html web tester to play around with realtime generation on the L40s)
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atasoglu 
posted an update 2 months ago
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Introducing ToolsGen 🛠️

I built a tool to solve a problem I kept running into: creating quality datasets for training LLMs to use tools.

ToolsGen takes your JSON tool definitions and automatically generates realistic user requests, corresponding tool calls, and evaluates them using an LLM-as-a-judge pipeline. It outputs datasets ready to use with Hugging Face.

What makes it useful:
- Generates realistic user requests + tool calls from JSON definitions
- LLM-as-a-judge quality scoring with multi-dimensional rubrics
- Multiple sampling strategies (random, parameter-aware, semantic)
- OpenAI-compatible API support
- Outputs JSONL with train/val splits

Still early days (API isn't stable yet), but it's already helping me generate tool-calling datasets much faster.

Check it out: https://github.com/atasoglu/toolsgen

Happy to hear feedback or ideas!
pagezyhf 
posted an update 2 months ago
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🚀 Big news for AI builders!

We’re thrilled to announce that the Qwen3-VL family of vision-language models is now available on Azure AI Foundry, thanks to our collaboration with Microsoft.

We bring open-source innovation to enterprise-grade AI infrastructure, making it easier than ever for enterprise to deploy and scale the latest and greatest from models from hugging Face securely within Azure.

🔍 Highlights:

- Deploy Qwen3-VL instantly via managed endpoints
- Built-in governance, telemetry, and lifecycle management
- True multimodal reasoning — vision, language, and code understanding
- State-of-the-art performance, outperforming closed-source models like Gemini 2.5 Pro and GPT-5
- Available in both *Instruct* and *Thinking* modes, across 24 model sizes

👉 Get started today: search for Qwen3-VL in the Hugging Face Collection on Azure AI Foundry.
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pagezyhf 
posted an update 4 months ago
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What’s your biggest headache deploying Hugging Face models to the cloud—and how can we fix it for you?
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pagezyhf 
posted an update 4 months ago
pagezyhf 
posted an update 4 months ago
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🤝 Collaborating with AMD to ensure Hugging Face Transformers runs smoothly on AMD GPUs!

We run daily CI on AMD MI325 to track the health of the most important model architectures and we’ve just made our internal dashboard public.

By making this easily accessible, we hope to spark community contributions and improve support for everyone!
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yjernite 
posted an update 4 months ago
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Tremendous quality of life upgrade on the Hugging Face Hub - we now have auto-complete emojis 🤗 🥳 👏 🙌 🎉

Get ready for lots more very serious analysis on a whole range of topics from yours truly now that we have unlocked this full range of expression 😄 🤔 🗣 🙊
ariG23498 
posted an update 4 months ago
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New post is live!

This time we cover some major updates to transformers.

🤗
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Abhaykoul 
posted an update 4 months ago
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🚀 Ever dreamed of training your own Large Language Model from scratch? What if I told you it doesn't require a supercomputer or PhD in ML? 🤯

Introducing LLM Trainer - the educational framework that makes LLM training accessible to EVERYONE! Whether you're on a CPU-only laptop or scaling to distributed GPUs, we've got you covered. 💻➡️🖥️

Why LLM Trainer? Because existing tools are either too simplistic (hiding the magic) or too complex (requiring expert knowledge). We bridge the gap with:

🎓 Educational transparency - every component built from scratch with clear code
💻 CPU-first approach - start training immediately, no GPU needed
🔧 Full customization - modify anything you want
📈 Seamless scaling - from laptop to cluster without code changes
🤝 HuggingFace integration - works with existing models & tokenizers

Key highlights:
✅ Built-in tokenizers (BPE, WordPiece, HF wrappers)
✅ Complete Transformer implementation from scratch
✅ Optimized for CPU training
✅ Advanced features: mixed precision, gradient checkpointing, multiple generation strategies
✅ Comprehensive monitoring & metrics

Perfect for:
- Students learning transformers
- Researchers prototyping new ideas
- Developers building domain-specific models

Ready to train your first LLM? It's easier than you think!

🔗 Check it out: https://github.com/HelpingAI/llm-trainer
📚 Docs: Getting Started Guide
💬 Join the community: GitHub Discussions

#AI #MachineLearning #LLM #DeepLearning #OpenSource #Python #HuggingFace #NLP

Special thanks to HuggingFace and PyTorch teams for the amazing ecosystem! 🙏
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