Dev Mode Explorers

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AtAndDevΒ 
posted an update about 15 hours ago
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There seems to multiple paid apps shared here that are based on models on hf, but some ppl sell their wrappers as "products" and promote them here. For a long time, hf was the best and only platform to do oss model stuff but with the recent AI website builders anyone can create a product (really crappy ones btw) and try to sell it with no contribution to oss stuff. Please dont do this, or try finetuning the models you use...
Sorry for filling yall feed with this bs but yk...
m-ricΒ 
posted an update 1 day ago
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smolagents now support vLLM! πŸ₯³

As one of the most popular local inference solutions, the community had been asking us to integrate vLLM: after a heavy refactoring of our LLM classes, we've just released smolagents 1.11.0, with a brand new VLLMModel class.

Go try it and tell us what you think!

https://github.com/huggingface/smolagents/blob/45b2c86857b7f7657daaa74e4d17d347e9e2c4a4/src/smolagents/models.py#L497
fdaudensΒ 
posted an update 3 days ago
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🀯 Gemma 3's image analysis blew me away!

Tested 2 ways to extract airplane registration numbers from photos with 12B model:

1️⃣ Gradio app w/API link (underrated feature IMO) + ZeroGPU infra on Hugging Face in Google Colab. Fast & free.

2️⃣ LMStudio + local processing (100% private). Running this powerhouse on a MacBook w/16GB RAM is wild! πŸš€

Colab: https://colab.research.google.com/drive/1YmmaP0IDEu98CLDppAAK9kbQZ7lFnLZ1?usp=sharing
AtAndDevΒ 
posted an update 4 days ago
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Gemma 3 seems to be really good at human preference. Just waiting for ppl to see it.
fdaudensΒ 
posted an update 4 days ago
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Ever wanted 45 min with one of AI’s most fascinating minds? Was with @thomwolf at HumanX Vegas. Sharing my notes of his Q&A with the pressβ€”completely changed how I think about AI’s future:

1️⃣ The next wave of successful AI companies won’t be defined by who has the best model but by who builds the most useful real-world solutions. "We all have engines in our cars, but that’s rarely the only reason we buy one. We expect it to work well, and that’s enough. LLMs will be the same."

2️⃣ Big players are pivoting: "Closed-source companiesβ€”OpenAI being the firstβ€”have largely shifted from LLM announcements to product announcements."

3️⃣ Open source is changing everything: "DeepSeek was open source AI’s ChatGPT moment. Basically, everyone outside the bubble realized you can get a model for freeβ€”and it’s just as good as the paid ones."

4️⃣ Product innovation is being democratized: Take Manus, for exampleβ€”they built a product on top of Anthropic’s models that’s "actually better than Anthropic’s own product for now, in terms of agents." This proves that anyone can build great products with existing models.

We’re entering a "multi-LLM world," where models are becoming commoditized, and all the tools to build are readily availableβ€”just look at the flurry of daily new releases on Hugging Face.

Thom's comparison to the internet era is spot-on: "In the beginning you made a lot of money by making websites... but nowadays the huge internet companies are not the companies that built websites. Like Airbnb, Uber, Facebook, they just use the internet as a medium to make something for real life use cases."

Love to hear your thoughts on this shift!
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freddyaboultonΒ 
posted an update 5 days ago
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Privacy matters when talking to AI! πŸ”‡

We've just added a microphone mute button to FastRTC in our latest update (v0.0.14). Now you control exactly what your LLM hears.

Plus lots more features in this release! Check them out:
https://github.com/freddyaboulton/fastrtc/releases/tag/0.0.14
fdaudensΒ 
posted an update 5 days ago
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πŸ”₯The Open R1 team just dropped OlympicCoder and it's wild:

- 7B model outperforms Claude 3.7 Sonnet on IOI benchmark (yes, 7B!!)
- 32B crushes all open-weight models tested, even those 100x larger 🀯

Open-sourcing the future of code reasoning! πŸš€

Check it out https://huggingface.co/blog/open-r1/update-3
julien-cΒ 
posted an update 5 days ago
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Important notice 🚨

For Inference Providers who have built support for our Billing API (currently: Fal, Novita, HF-Inference – with more coming soon), we've started enabling Pay as you go (=PAYG)

What this means is that you can use those Inference Providers beyond the free included credits, and they're charged to your HF account.

You can see it on this view: any provider that does not have a "Billing disabled" badge, is PAYG-compatible.
BrigitteTousiΒ 
posted an update 5 days ago
m-ricΒ 
posted an update 6 days ago
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Our new Agentic leaderboard is now live!πŸ’₯

If you ever asked which LLM is best for powering agents, we've just made a leaderboard that ranks them all! Built with @albertvillanova , this ranks LLMs powering a smolagents CodeAgent on subsets of various benchmarks. βœ…

πŸ† GPT-4.5 comes on top, even beating reasoning models like DeepSeek-R1 or o1. And Claude-3.7-Sonnet is a close second!

The leaderboard also allows you to show the scores of vanilla LLMs (without any agentic setup) on the same benchmarks: this shows the huge improvements brought by agentic setups. πŸ’ͺ

(Note that results will be added manually, so the leaderboard might not always have the latest LLMs)
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BrigitteTousiΒ 
posted an update 6 days ago
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Regardless of X being down or not, so glad I can rely on HF Posts for AI news β€οΈπŸ€—
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fdaudensΒ 
posted an update 7 days ago
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Honored to be named among their 12 pioneers and power players in the news industry in the 2025 Tech Trends Report from Future Today Strategy Group.

Incredible group to be part of - each person is doing groundbreaking work at the intersection of AI and journalism. Worth following them all: they're consistently sharing practical insights on building the future of news.

Take the time to read this report, it's packed with insights as always. The news & information section's #1 insight hits hard: "The most substantive economic impact of AI to date has been licensing payouts for a handful of big publishers. The competition will start shifting in the year ahead to separate AI 'haves' that have positioned themselves to grow from the 'have-nots.'"

This AI-driven divide is something I've been really concerned about. Now is the time to build more than ever!

πŸ‘‰ Full report here: https://ftsg.com/wp-content/uploads/2025/03/FTSG_2025_TR_FINAL_LINKED.pdf
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mcpotatoΒ 
posted an update 10 days ago
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Stoked to announce we've partnered with JFrog to continue improving safety on the Hub! 🐸

Their model scanner brings new scanning capabilities to the table, aimed at reducing alert fatigue.

More on that in our blog post: https://huggingface.co/blog/jfrog
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fdaudensΒ 
posted an update 10 days ago
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AI will bring us "a country of yes-men on servers" instead of one of "Einsteins sitting in a data center" if we continue on current trends.

Must-read by @thomwolf deflating overblown AI promises and explaining what real scientific breakthroughs require.

https://thomwolf.io/blog/scientific-ai.html
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fdaudensΒ 
posted an update 17 days ago
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What if AI becomes as ubiquitous as the internet, but runs locally and transparently on our devices?

Fascinating TED talk by @thomwolf on open source AI and its future impact.

Imagine this for AI: instead of black box models running in distant data centers, we get transparent AI that runs locally on our phones and laptops, often without needing internet access. If the original team moves on? No problem - resilience is one of the beauties of open source. Anyone (companies, collectives, or individuals) can adapt and fix these models.

This is a compelling vision of AI's future that solves many of today's concerns around AI transparency and centralized control.

Watch the full talk here: https://www.ted.com/talks/thomas_wolf_what_if_ai_just_works
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fdaudensΒ 
posted an update 18 days ago
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Is this the best tool to extract clean info from PDFs, handwriting and complex documents yet?

Open source olmOCR just dropped and the results are impressive.

Tested the free demo with various documents, including a handwritten Claes Oldenburg letter. The speed is impressive: 3000 tokens/second on your own GPU - that's 1/32 the cost of GPT-4o ($190/million pages). Game-changer for content extraction and digital archives.

To achieve this, Ai2 trained a 7B vision language model on 260K pages from 100K PDFs using "document anchoring" - combining PDF metadata with page images.

Best part: it actually understands document structure (columns, tables, equations) instead of just jumbling everything together like most OCR tools. Their human eval results back this up.

πŸ‘‰ Try the demo: https://olmocr.allenai.org

Going right into the AI toolkit: JournalistsonHF/ai-toolkit
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freddyaboultonΒ 
posted an update 19 days ago
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Getting WebRTC and Websockets right in python is very tricky. If you've tried to wrap an LLM in a real-time audio layer then you know what I'm talking about.

That's where FastRTC comes in! It makes WebRTC and Websocket streams super easy with minimal code and overhead.

Check out our org: hf.co/fastrtc
fdaudensΒ 
posted an update 20 days ago
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πŸš€ Just launched: A toolkit of 20 powerful AI tools that journalists can use right now - transcribe, analyze, create. 100% free & open-source.

Been testing all these tools myself and created a searchable collection of the most practical ones - from audio transcription to image generation to document analysis. No coding needed, no expensive subscriptions.

Some highlights I've tested personally:
- Private, on-device transcription with speaker ID in 100+ languages using Whisper
- Website scraping that just works - paste a URL, get structured data
- Local image editing with tools like Finegrain (impressive results)
- Document chat using Qwen 2.5 72B (handles technical papers well)

Sharing this early because the best tools come from the community. Drop your favorite tools in the comments or join the discussion on what to add next!

πŸ‘‰ JournalistsonHF/ai-toolkit
m-ricΒ 
posted an update 21 days ago
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We now have a Deep Research for academia: SurveyX automatically writes academic surveys nearly indistinguishable from human-written ones πŸ”₯

Researchers from Beijing and Shanghai just published the first application of a deep research system to academia: their algorithm, given a question, can give you a survey of all papers on the subject.

To make a research survey, you generally follow two steps, preparation (collect and organize papers) and writing (outline creation, writing, polishing). Researchers followed the same two steps and automated them.

🎯 For the preparation part, a key part is find all the important references on the given subject.
Researchers first cast a wide net of all relevant papers. But then finding the really important ones is like distilling knowledge from a haystack of information. To solve this challenge, they built an β€œAttributeTree” object that structures key information from citations. Ablating these AttributeTrees significantly decreased structure and synthesis scores, so they were really useful!

πŸ“ For the writing part, key was to get a synthesis that's both short and true. This is not easy to get with LLMs! So they used methods like LLM-based deduplication to shorten the too verbose listings made by LLMs, and RAG to grab original quotes instead of made-up ones.

As a result, their system outperforms previous approaches by far!

As assessed by LLM-judges, the quality score os SurveyX even approaches this of human experts, with 4.59/5 vs 4.75/5 πŸ†

I advise you to read the paper, it's a great overview of the kind of assistants that we'll get in the short future! πŸ‘‰ SurveyX: Academic Survey Automation via Large Language Models (2502.14776)
Their website shows examples of generated surveys πŸ‘‰ http://www.surveyx.cn/
fdaudensΒ 
posted an update 23 days ago