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Earth Observation Datasets

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mikonvergence  updated a dataset 4 days ago
Major-TOM/Core-AlphaEarth-Embeddings
mikonvergence  updated a Space 4 days ago
Major-TOM/README
Smith42  authored a paper 28 days ago
AstroLLaVA: towards the unification of astronomical data and natural language
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Nymbo 
posted an update 1 day ago
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I built a general use MCP space ~ Fetch webpages, DuckDuckGo search, Python code execution, Kokoro TTS, Image Gen, Video Gen.

# Tools

1. Fetch webpage
2. Web search via DuckDuckGo (very concise, low excess context)
3. Python code executor
4. Kokoro-82M speech generation
5. Image Generation (use any model from HF Inference Providers)
6. Video Generation (use any model from HF Inference Providers)

The first four tools can be used without any API keys whatsoever. DDG search is free and the code execution and speech gen is done on CPU. Having a HF_READ_TOKEN in the env variables will show all tools. If there isn't a key present, The Image/Video Gen tools are hidden.

Nymbo/Tools
mikonvergence 
posted an update 4 days ago
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𝐌𝐚𝐣𝐨𝐫 𝐓𝐎𝐌 ➕ 𝐆𝐨𝐨𝐠𝐥𝐞 𝐃𝐞𝐞𝐩𝐌𝐢𝐧𝐝'𝐬 𝐀𝐥𝐩𝐡𝐚𝐄𝐚𝐫𝐭𝐡 𝐄𝐦𝐛𝐞𝐝𝐝𝐢𝐧𝐠𝐬 𝐚𝐫𝐞 𝐧𝐨𝐰 𝐚𝐯𝐚𝐢𝐥𝐚𝐛𝐥𝐞 ‼️

This is a tiny (about 6 TB of data, but only 62,489 grid cells of ~100 sqkm) prototype dataset that allows to instantly connect existing Major TOM data with AlphaEarth embeddings.

Major-TOM/Core-AlphaEarth-Embeddings

I curated it to support several relevant research projects, but I figured it could help more people in the community to experiment and explore new applications of AlphaEarth.

𝐃𝐢𝐫𝐞𝐜𝐭𝐢𝐨𝐧𝐬 𝐟𝐨𝐫 𝐔𝐬𝐞
Each embedding sample comes from the original annual dataset produced by Google DeepMind. It means that, unlike samples from Sentinel-2 or Sentinel-1, it contains aggregated annual information from a particular year and is not linked to one particular observation. The existing Major TOM samples from physical sensors provide information potentially (and likely) contained in the AlphaEarth embedding sample, but they miss the temporal component represented within AEF embedding fields.

For more information, please check the dataset card on HuggingFace.

⚠️ 𝐖𝐀𝐑𝐍𝐈𝐍𝐆: 𝐄𝐦𝐛𝐞𝐝𝐝𝐢𝐧𝐠𝐬 𝐢𝐧 𝐭𝐡𝐢𝐬 𝐝𝐚𝐭𝐚𝐬𝐞𝐭 𝐝𝐨 𝐧𝐨𝐭 𝐫𝐞𝐩𝐫𝐞𝐬𝐞𝐧𝐭 𝐢𝐧𝐝𝐢𝐯𝐢𝐝𝐮𝐚𝐥 𝐬𝐚𝐦𝐩𝐥𝐞𝐬, 𝐛𝐮𝐭 𝐚 𝐰𝐡𝐨𝐥𝐞 𝐲𝐞𝐚𝐫 𝐨𝐟 𝐦𝐮𝐥𝐭𝐢-𝐦𝐨𝐝𝐚𝐥 𝐨𝐛𝐬𝐞𝐫𝐯𝐚𝐭𝐢𝐨𝐧𝐬. 𝐇𝐚𝐯𝐞 𝐟𝐮𝐧!

🙏 Built on top of fantastic work of
Christopher Brown, Michal Kazmierski, Valerie Pasquarella, Emily Schechter and others at Google DeepMind.
mikonvergence 
updated a dataset 4 days ago
mikonvergence 
updated a Space 4 days ago
Nymbo 
posted an update 10 days ago
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Anyone using Jan-v1-4B for local MCP-based web search, I highly recommend you try out Intelligent-Internet/II-Search-4B

Very impressed with this lil guy and it deserves more downloads. It's based on the original version of Qwen3-4B but find that it questions reality way less often. Jan-v1 seems to think that everything it sees is synthetic data and constantly gaslights me
fdaudens 
posted an update 12 days ago
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Want to learn to build an AI Agent? I put together a cookbook for creating your own news research agent with OpenAI GPT-OSS:

- Searches headlines & specific sites
- Pulls full articles when you need depth
- Summarizes with clickable sources
- Runs in a simple Gradio chat UI
- No GPU, no local setup — just open-weight GPT-OSS models via Hugging Face

If you’ve been wanting to try agents but weren’t sure where to start, this is an end-to-end example you can fork, run, and adapt.

Full guide + code https://huggingface.co/blog/fdaudens/openai-gpt-oss-agent-inference-providers
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fdaudens 
posted an update 14 days ago
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What can OpenAI’s new open models do with the news? I built a News Agent to find out.

It can answer questions about the news in real time, and every answer comes with original source links so you can dive deeper.

Ask it things like:
- "What are the top news stories today?"
- "What's the latest on artificial intelligence?"
- Follow-up questions on specific stories

Runs with Hugging Face inference providers, letting you compare results from the OpenAI 20B and 120B models

So far, I’m quite impressed by the capabilities of even the smaller 20B model. Definitely not a perfect project, but curious to hear your thoughts!

fdaudens/gpt-oss-news-agent
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fdaudens 
posted an update 15 days ago
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OpenAI’s GPT-OSS has sparked ~400 new models on Hugging Face and racked up 5M downloads in less than a week, already outpacing DeepSeek R1’s first-week numbers.

For comparison: when R1 launched, I tracked 550 derivatives (across 8 base models) in a week, with ~3M downloads. GPT-OSS is ahead on adoption and engagement.

It’s also the most-liked release of any major LLM this summer. The 20B and 120B versions quickly shot past Kimi K2, GLM 4.5, and others in likes.

Most-downloaded GPT-OSS models include LM Studio and Unsloth AI versions:
1️⃣ openai/gpt-oss-20b - 2.0M
2️⃣ lmstudio-community/gpt-oss-20b-MLX-8bit - 750K
3️⃣ openai/gpt-oss-120b - 430K
4️⃣ unsloth/gpt-oss-20b-GGUF - 380K
5️⃣ lmstudio-community/gpt-oss-20b-GGUF - 330K

The 20B version is clearly finding its audience, showing the power of smaller, faster, more memory- and energy-efficient models. (These numbers don’t include calls to the models via inference providers, so the real usage is likely even bigger, especially for the 120B version)

Open-weight models let anyone build on top. Empower the builders, and innovation takes off. 🚀
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clem 
posted an update 19 days ago
fdaudens 
posted an update 20 days ago
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Well, it took just 2 hours for openai/gpt-oss-120b to hit #1 on Hugging Face. Don’t remember seeing anything rise that fast!
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Smith42 
authored a paper 28 days ago
fdaudens 
posted an update about 1 month ago
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AudioRAG is becoming real! Just built a demo with ColQwen-Omni that does semantic search on raw audio, no transcription needed.

Drop in a podcast, ask your question, and it finds the exact chunks where it happens. You can also get a written answer.

What’s exciting: it skips transcription, making it faster and better at capturing emotion, ambient sound, and tone, surfacing results text search would miss.

- Demo: fdaudens/colqwen-omni-demo
- Blog post from ColQwen team: https://huggingface.co/blog/manu/colqwen-omni-omnimodal-retrieval
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fdaudens 
posted an update about 1 month ago
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You might not have heard of Moonshot AI — but within 24 hours, their new model Kimi K2 shot to the top of Hugging Face’s trending leaderboard.

So… who are they, and why does it matter?

Had a lot of fun co-writing this blog post with @xianbao , with key insights translated from Chinese, to unpack how this startup built a model that outperforms GPT-4.1, Claude Opus, and DeepSeek V3 on several major benchmarks.

🧵 A few standout facts:

1. From zero to $3.3B in 18 months:
Founded in March 2023, Moonshot is now backed by Alibaba, Tencent, Meituan, and HongShan.

2. A CEO who thinks from the end:
Yang Zhilin (31) previously worked at Meta AI, Google Brain, and Carnegie Mellon. His vision? Nothing less than AGI — still a rare ambition among Chinese AI labs.

3. A trillion-parameter model that’s surprisingly efficient:
Kimi K2 uses a mixture-of-experts architecture (32B active params per inference) and dominates on coding/math benchmarks.

4. The secret weapon: Muon optimizer:
A new training method that doubles efficiency, cuts memory in half, and ran 15.5T tokens with zero failures. Big implications.

Most importantly, their move from closed to open source signals a broader shift in China’s AI scene — following Baidu’s pivot. But as Yang puts it: “Users are the only real leaderboard.”

👇 Check out the full post to explore what Kimi K2 can do, how to try it, and why it matters for the future of open-source LLMs:
https://huggingface.co/blog/fdaudens/moonshot-ai-kimi-k2-explained
fdaudens 
posted an update about 1 month ago
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AI is reshaping everything—how we work, how we feel, even how nations compete.

Today’s reads cut across power, emotion, and disruption.

Here’s what stood out and why it matters 👇

AI might “solve” loneliness, but this could be a problem, as the discomfort of loneliness shapes us in important ways. 💔 https://t.co/k2Q9le6G0P

A new study warns of significant risks in using AI therapy chatbots, highlighting issues like stigmatization and inappropriate responses. 🤖 https://t.co/EFyW0RbYVl

AI is already showing signs of slashing job openings in the UK, particularly in roles exposed to the technology, suggesting a labor market slowdown. 📉 https://t.co/hhs0BbqIMa

AI firms like OpenAI are poaching Wall Street quants with massive paydays, shifting the talent landscape for building artificial general intelligence. 💰 https://www.businessinsider.com/ai-talent-openai-wall-street-quant-trading-firms-2025-7

Speaking of which: Nvidia CEO Jensen Huang disagrees with Anthropic CEO Dario Amodei on whether AI will create more jobs—or trigger a “white-collar apocalypse.” Huang believes AI will create vastly more, and better, jobs. ⚔️ https://t.co/YHWhY7qvSq

Can Nvidia convince governments to pay for “sovereign AI”? Politicians are warming to the idea of national AI systems, but it might not reduce dependence on US tech. 🌍 https://t.co/htQDzJAIDu
louisbrulenaudet 
posted an update about 2 months ago
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Because hackathons are often the starting point for many AI projects, I've created a Python-backend template incorporating my feedback to streamline collaboration and urgent deployments 🏎️

Within a year, I had the opportunity to participate in hackathons organized by Mistral, OpenAI, and DeepMind and this GitHub template is structured around several fundamental building blocks and recommendations I offer developers eager to participate in their first hackathon, whether as part of a team or individually. Its emphasis is on rapid setup and deployment through:
- uv as a package manager, simplifying usage via a series of pre-configured make commands.
- FastAPI for API management, structured in a modular architecture designed to minimize branch conflicts during merges to main branches (using minimal health-check and ping routes to verify Docker’s proper execution and backend accessibility on the local network).
- Pydantic for validation and type handling, which simplifies debugging and enhances understanding of data objects.
- A set of custom instructions tailored for agents (Cline and GitHub Copilot), aimed at improving overall comprehension of the application and optimizing the vibe-coding experience.

This template includes unit tests with a 100% success rate and test coverage, as well as a minimal CI file ensuring that the FastAPI application runs correctly. Thus, merging code that breaks the server into production becomes impossible ⛔️

In general, I would reiterate an essential piece of advice: your two main adversaries are branch conflicts—particularly when the same file is modified concurrently within a brief period, especially if your architecture isn’t built for scalability—and deployment issues under urgent circumstances ⏱️

Link to GitHub: https://github.com/louisbrulenaudet/hackathon-backend

Simply issue these commands and you can ship your code at the speed of light:
make init
make dev
harshinde 
authored a paper about 2 months ago
Nymbo 
posted an update about 2 months ago
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Anyone know how to reset Claude web's MCP config? I connected mine when the HF MCP first released with just the default example spaces added. I added lots of other MCP spaces but Claude.ai doesn't update the available tools... "Disconnecting" the HF integration does nothing, deleting it and adding it again does nothing.

Refreshing tools works fine in VS Code because I can manually restart it in mcp.json, but claude.ai has no such option. Anyone got any ideas?
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fdaudens 
posted an update about 2 months ago
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Three big AI copyright updates this week alone. Tracking it all is getting almost impossible!

That’s why @BrigitteTousi and I built this interactive tracker to keep you up to date fdaudens/ai-copyright-lawsuits

(Prototyped in minutes with DeepSite!)
fdaudens 
posted an update 2 months ago
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This is what efficient AI looks like: Gemma 3n just dropped - a natively multimodal model that runs entirely on your device. No cloud. No API calls.

🧠 Text, image, audio, and video - handled locally.
⚡️Only needs 2B in GPU memory to run
🤯 First sub-10B model to hit 1300+ Elo
✅ Plug-and-play with Hugging Face, MLX, llama.cpp, and more.

Plus: Multilingual out of the box (140+ languages), fine-tune in a free Colab notebook.

google/gemma-3n-685065323f5984ef315c93f4
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fdaudens 
posted an update 2 months ago
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ASMR Shiba has something to say 🐾