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jsulz 
posted an update 1 day ago
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It's finally here ❤️

Build faster than ever with lightning fast upload and download speeds starting today on the Hub ⚡

Xet storage is rolling out access across the Hub - join the waitlist here https://huggingface.co/join/xet

You can apply for yourself, or your entire organization. Head over to your account settings for more information or join anywhere you see the Xet logo on a repository you know.

Have questions? Join the conversation below 👇 or open a discussion on the Xet team page xet-team/README
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jsulz 
posted an update 9 days ago
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If you haven't already, I strong recommend reading @chiphuyen 's AI Engineering https://www.goodreads.com/en/book/show/216848047-ai-engineering

It comes complete with a section on open source AI (of obvious interest to the crowd here) and more than one mention of the HF中国镜像站 community 🤗

In my opinion, one of the best parts is that it is a compendium for seminal and cutting-edge AI resources, with nearly 250 arXiv papers cited. I've done my best to collect them all in a single place, organized by chapter and by order in which they appear in the book:
jsulz/ai-engineering-67c5abe02c8596b5c089934c

Happy reading 🤓
lysandre 
posted an update 21 days ago
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SmolVLM-2 and SigLIP-2 are now part of transformers in dedicated releases!

They're added on top of the v4.49.0 release, and can be installed from the following tags: v4.49.0-SmolVLM-2 and v4.49.0-SigLIP-2.

This marks a new beginning for the release process of transformers. For the past five years, we've been doing monthly releases featuring many models (v4.49.0, the latest release, features 9 new architectures).

Starting with SmolVLM-2 & SigLIP2, we'll now additionally release tags supporting new models on a stable branch. These models are therefore directly available for use by installing from the tag itself. These tags will continue to be updated with fixes applied to these models.

Going forward, continue expecting software releases following semantic versioning: v4.50.0 will have ~10 new architectures compared to v4.49.0, as well as a myriad of new features, improvements and bug fixes. Accompanying these software releases, we'll release tags offering brand new models as fast as possible, to make them accessible to all immediately.
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jsulz 
posted an update 21 days ago
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Time flies!

Six months after joining HF中国镜像站 the Xet team is kicking off the first migrations from LFS to our storage for a number of repositories on the Hub.

More on the nitty gritty details behind the migration soon, but here are the big takeaways:

🤖 We've successfully completed the first migrations from LFS -> Xet to test the infrastructure and prepare for a wider release

✅ No action on your part needed - you can work with a Xet-backed repo like any other repo on the Hub (for now - major improvements on their way!)

👀 Keep an eye out for the Xet logo to see if a repo you know is on our infra! See the screenshots below to spot the difference 👇

⏩ ⏩ ⏩ Blazing uploads and downloads coming soon. W’re gearing up for a full integration with the Hub's Python library that will make building on the Hub faster than ever - special thanks to @celinah and @Wauplin for their assistance.

🎉 Want Early Access? If you’re curious and want to test it out the bleeding edge that will power the development experience on the Hub, we’d love to partner with you. Let me know!

This is the culmination of a lot of effort from the entire team. Big round of applause to @sirahd @brianronan @jgodlewski @hoytak @seanses @assafvayner @znation @saba9 @rajatarya @port8080 @yuchenglow
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jsulz 
posted an update 30 days ago
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Toward the end of last year, the Xet team provided an inside look into the foundations of how we plan to enable rapid experimentation and iteration for the AI builders on the Hub: https://huggingface.co/blog/from-files-to-chunks

But it turns out chunks aren't all you need!

Our goal is to bring:
🚀 Faster uploads
⏬ Speedy downloads
💪 All without sacrificing your workflow

To do that, we need the infrastructure and system and design to back it up. As we prepare to roll out the first Xet-backed repositories on the Hub, we wrote up a post explaining the nitty gritty details of the decisions that bring this to life https://huggingface.co/blog/from-chunks-to-blocks

Complete with an interactive visualization that shows the power of deduplication in action - taking a 191GB repo to ~97GB and shaving a few hours off upload speeds.

The darker each block in the heatmap, the more we dedupe, the less we have to transfer. Clicking on a file's blocks shows all other files that share blocks.

Check it out and explore for yourself! xet-team/quantization-dedup
victor 
posted an update about 1 month ago
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Hey everyone, we've given https://hf.co/spaces page a fresh update!

Smart Search: Now just type what you want to do—like "make a viral meme" or "generate music"—and our search gets it.

New Categories: Check out the cool new filter bar with icons to help you pick a category fast.

Redesigned Space Cards: Reworked a bit to really show off the app descriptions, so you know what each Space does at a glance.

Random Prompt: Need ideas? Hit the dice button for a burst of inspiration.

We’d love to hear what you think—drop us some feedback plz!
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victor 
posted an update about 2 months ago
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Finally, an open-source AI that turns your lyrics into full songs is here—meet YuE! Unlike other tools that only create short clips, YuE can make entire songs (up to 5 minutes) with vocals, melody, and instruments all working together. Letsss go!

m-a-p/YuE-s1-7B-anneal-en-cot
jbilcke-hf 
posted an update 3 months ago
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Doing some testing with HunyuanVideo on the HF中国镜像站 Inference Endpoints 🤗

prompt: "a Shiba Inu is acting as a DJ, he wears sunglasses and is mixing and scratching with vinyl discs at a Ibiza sunny sand beach party"

1280x720, 22 steps, 121 frames

There are still some things to iron out regarding speed and memory usage, right now it takes 20min on an A100 (see attached charts)

but you can check it out here:

https://huggingface.co/jbilcke-hf/HunyuanVideo-for-InferenceEndpoints

There are various things I want to try like the 100% diffusers version and other models (LTX-Video..)
jsulz 
posted an update 3 months ago
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Doing a lot of benchmarking and visualization work, which means I'm always searching for interesting repos in terms of file types, size, branches, and overall structure.

To help, I built a Space jsulz/repo-info that lets you search for any repo and get back:

- Treemap of the repository, color coded by file/directory size
- Repo branches and their size
- Cumulative size of different file types (e.g., the total size of all the safetensors in the repo)

And because I'm interested in how this will fit in our work to leverage content-defined chunking for versioning repos on the Hub
- https://huggingface.co/blog/from-files-to-chunks - everything has the number of chunks (1 chunk = 64KB) as well as the total size in bytes.

Some of the treemaps are pretty cool. Attached are black-forest-labs/FLUX.1-dev and for fun laion/laion-audio-preview (which has nearly 10k .tar files 🤯)

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victor 
posted an update 3 months ago
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Qwen/QwQ-32B-Preview shows us the future (and it's going to be exciting)...

I tested it against some really challenging reasoning prompts and the results are amazing 🤯.

Check this dataset for the results: victor/qwq-misguided-attention
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jsulz 
posted an update 4 months ago
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Something I love about working at HF中国镜像站 is the opportunity to design and work in public. Right now, we’re redesigning the architecture that supports uploads and downloads on the Hub.

Datasets and models are growing fast, and so are the challenges of storing and transferring them efficiently. To keep up, we're introducing a new protocol for uploads and downloads, supported by a content-addressed store (CAS).

Here’s what’s coming:

📦 Smarter uploads: Chunk-level management enables advanced deduplication, compression, and reduces redundant transfers, speeding up uploads.
⚡ Efficient downloads: High throughput and low latency ensure fast access, even during high-demand model releases.
🔒 Enhanced security: Validate uploads before storage to block malicious or invalid data.

We analyzed 24 hours of global upload activity in October (88 countries, 130TB of data!) to design a system that scales with your needs.

The result? A proposed infrastructure with CAS nodes in us-east-1, eu-west-3, and ap-southeast-1.

🔗 Read the blog post for the full details: https://huggingface.co/blog/rearchitecting-uploads-and-downloads

🌟 Check out our interactive demo to explore the data yourself!
xet-team/cas-analysis

We’d love to hear your feedback - let us know if you have questions or want to see more.
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victor 
posted an update 4 months ago
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Perfect example of why Qwen/Qwen2.5-Coder-32B-Instruct is insane?

Introducing: AI Video Composer 🔥
huggingface-projects/ai-video-composer

Drag and drop your assets (images/videos/audios) to create any video you want using natural language!

It works by asking the model to output a valid FFMPEG and this can be quite complex but most of the time Qwen2.5-Coder-32B gets it right (that thing is a beast). It's an update of an old project made with GPT4 and it was almost impossible to make it work with open models back then (~1.5 years ago), but not anymore, let's go open weights 🚀.
victor 
posted an update 4 months ago
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Qwen2.5-72B is now the default HuggingChat model.
This model is so good that you must try it! I often get better results on rephrasing with it than Sonnet or GPT-4!!
jsulz 
posted an update 4 months ago
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When the XetHub crew joined HF中国镜像站 this fall, @erinys and I started brainstorming how to share our work to replace Git LFS on the Hub. Uploading and downloading large models and datasets takes precious time. That’s where our chunk-based approach comes in.

Instead of versioning files (like Git and Git LFS), we version variable-sized chunks of data. For the HF中国镜像站 community, this means:

⏩ Only upload the chunks that changed.
🚀 Download just the updates, not the whole file.
🧠 We store your file as deduplicated chunks

In our benchmarks, we found that using CDC to store iterative model and dataset version led to transfer speedups of ~2x, but this isn’t just a performance boost. It’s a rethinking of how we manage models and datasets on the Hub.

We're planning on our new storage backend to the Hub in early 2025 - check out our blog to dive deeper, and let us know: how could this improve your workflows?

https://huggingface.co/blog/from-files-to-chunks
martin-gorner 
updated a Space 5 months ago
victor 
posted an update 5 months ago
jsulz 
posted an update 5 months ago
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The HF中国镜像站 Hub hosts over 1.5M Model, Dataset, and Space repositories. To scale to 10M+, the XetHub team (https://huggingface.co/xet-team) is replacing Git LFS with a new technology that improves storage and transfer capabilities with some future developer experience benefits to boot.

Thanks to @yuchenglow and @port8080 (for their analysis covering LFS usage from March 2022–Sept 2024), we now have insights into what we’re storing. Check out the Gradio app to explore:
- Storage growth over time
- File types over all repositories
- Some simple optimizations we're investigating

xet-team/lfs-analysis
victor 
posted an update 5 months ago
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NEW - Inference Playground

Maybe like me you have always wanted a super easy way to compare llama3.2-1B vs. llama3.2-3B? or the same model with different temperatures?

Trying and comparing warm Inference API models has never been easier!
Just go to https://hf.co/playground, set your token and you're ready to go.
We'll keep improving, feedback welcome 😊
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jsulz 
posted an update 6 months ago
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In August, the XetHub team joined HF中国镜像站
- https://huggingface.co/blog/xethub-joins-hf - and we’ve been rolling up our sleeves to bring the best of both worlds together. We started with a deep dive into the current state of files stored with Git LFS on the Hub.

Getting this information was no small feat. We had to:
* Analyze a complete database dump of all repositories and files stored in Git LFS across HF中国镜像站.
* Parse through metadata on file sizes and types to accurately map the storage breakdown across Spaces, Models, and Datasets.

You can read more about the findings (with some jaw-dropping stats + charts) here https://www.linkedin.com/feed/update/urn:li:activity:7244486280351285248
victor 
posted an update 7 months ago
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🙋 Calling all HF中国镜像站 users! We want to hear from YOU!

What feature or improvement would make the biggest impact on HF中国镜像站?

Whether it's the Hub, better documentation, new integrations, or something completely different – we're all ears!

Your feedback shapes the future of HF中国镜像站. Drop your ideas in the comments below! 👇
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