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Pedro Cuenca

pcuenq

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pcuenq's activity

reacted to merve's post with πŸ”₯πŸš€ about 20 hours ago
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2397
Interesting releases in open AI this week, let's recap 🀠 merve/feb-7-releases-67a5f7d7f172d8bfe0dd66f4

πŸ€– Robotics
> Pi0, first open-source foundation vision-language action model was released in Le Robot (Apache 2.0)

πŸ’¬ LLMs
> Groundbreaking: s1 is simpler approach to test-time scaling, the release comes with small s1K dataset of 1k question-reasoning trace pairs (from Gemini-Thinking Exp) they fine-tune Qwen2.5-32B-Instruct to get s1-32B, outperforming o1-preview on math 🀯 s1-32B and s1K is out!
> Adyen released DABstep, a new benchmark along with it's leaderboard demo for agents doing data analysis
> Krutrim released Krutrim-2 instruct, new 12B model based on NeMo12B trained and aligned on Indic languages, a new multilingual sentence embedding model (based on STSB-XLM-R), and a translation model for Indic languages

πŸ‘€ Multimodal
> PKU released Align-DS-V, a model aligned using their new technique called LLF for all modalities (image-text-audio), along with the dataset Align Anything
> OLA-7B is a new any-to-any model by Tencent that can take text, image, video, audio data with context window of 32k tokens and output text and speech in English and Chinese
> Krutrim released Chitrarth, a new vision language model for Indic languages and English

πŸ–ΌοΈ Vision
> BiRefNet_HR is a new higher resolution BiRefNet for background removal

πŸ—£οΈ Audio
> kyutai released Hibiki, it's a real-time speech-to-speech translation model 🀯 it's available for French-English translation
> Krutrim released Dhwani, a new STT model for Indic languages
> They also release a new dataset for STT-TTS

πŸ–ΌοΈ Image Generation
> Lumina released Lumina-Image-2.0, a 2B parameter-flow based DiT for text to image generation
> Tencent released Hunyuan3D-2, a 3D asset generation model based on DiT and Hunyuan3D-Paint
> boreal-hl-v1 is a new boring photorealistic image generation LoRA based on Hunyuan
reacted to burtenshaw's post with πŸš€πŸ€—β€οΈπŸ”₯ 22 days ago
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We’re launching a FREE and CERTIFIED course on Agents!

We're thrilled to announce the launch of the Hugging Face Agents course on Learn! This interactive, certified course will guide you through building and deploying your own AI agents.

Here's what you'll learn:

- Understanding Agents: We'll break down the fundamentals of AI agents, showing you how they use LLMs to perceive their environment (observations), reason about it (thoughts), and take actions. Think of a smart assistant that can book appointments, answer emails, or even write code based on your instructions.
- Building with Frameworks: You'll dive into popular agent frameworks like LangChain, LlamaIndex and smolagents. These tools provide the building blocks for creating complex agent behaviors.
- Real-World Applications: See how agents are used in practice, from automating SQL queries to generating code and summarizing complex documents.
- Certification: Earn a certification by completing the course modules, implementing a use case, and passing a benchmark assessment. This proves your skills in building and deploying AI agents.
Audience

This course is designed for anyone interested in the future of AI. Whether you're a developer, data scientist, or simply curious about AI, this course will equip you with the knowledge and skills to build your own intelligent agents.

Enroll today and start building the next generation of AI agent applications!

https://bit.ly/hf-learn-agents
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reacted to merve's post with ❀️πŸ”₯ about 1 month ago
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4856
supercharge your LLM apps with smolagents πŸ”₯

however cool your LLM is, without being agentic it can only go so far

enter smolagents: a new agent library by Hugging Face to make the LLM write code, do analysis and automate boring stuff!

Here's our blog for you to get started https://huggingface.co/blog/smolagents
reacted to fdaudens's post with πŸ‘ about 1 month ago
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2045
Running Gemma 2 2B at 41.66 tokens/s on my MacBook πŸ’»πŸš€

- MLX Community's swift conversion
- One-line download from the Hub
- Small yet powerful on-device model

Try it yourself: mlx-community/google-gemma2-667dca89bc9abbfa34080066

#GemmaAI #OnDeviceAI #MachineLearning
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reacted to reach-vb's post with πŸš€πŸ”₯ about 1 month ago
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4867
VLMs are going through quite an open revolution AND on-device friendly sizes:

1. Google DeepMind w/ PaliGemma2 - 3B, 10B & 28B: google/paligemma-2-release-67500e1e1dbfdd4dee27ba48

2. OpenGVLabs w/ InternVL 2.5 - 1B, 2B, 4B, 8B, 26B, 38B & 78B: https://huggingface.co/collections/OpenGVLab/internvl-25-673e1019b66e2218f68d7c1c

3. Qwen w/ Qwen 2 VL - 2B, 7B & 72B: Qwen/qwen2-vl-66cee7455501d7126940800d

4. Microsoft w/ FlorenceVL - 3B & 8B: https://huggingface.co/jiuhai

5. Moondream2 w/ 0.5B: https://huggingface.co/vikhyatk/

What a time to be alive! πŸ”₯
reacted to thomwolf's post with πŸ€—πŸ”₯πŸš€ about 1 month ago
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5406
We are proud to announce HuggingFaceFW/fineweb-2: A sparkling update to HuggingFaceFW/fineweb with 1000s of πŸ—£οΈlanguages.

We applied the same data-driven approach that led to SOTA English performance in🍷 FineWeb to thousands of languages.

πŸ₯‚ FineWeb2 has 8TB of compressed text data and outperforms other multilingual datasets in our experiments.

The dataset is released under the permissive πŸ“œ ODC-By 1.0 license, and the πŸ’» code to reproduce it and our evaluations is public.

We will very soon announce a big community project, and are working on a πŸ“ blogpost walking you through the entire dataset creation process. Stay tuned!

In the mean time come ask us question on our chat place: HuggingFaceFW/discussion

H/t @guipenedo @hynky @lvwerra as well as @vsabolcec Bettina Messmer @negar-foroutan and @mjaggi
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reacted to julien-c's post with πŸ€—β€οΈπŸ”₯ about 2 months ago
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After some heated discussion πŸ”₯, we clarify our intent re. storage limits on the Hub

TL;DR:
- public storage is free, and (unless blatant abuse) unlimited. We do ask that you consider upgrading to PRO and/or Enterprise Hub if possible
- private storage is paid above a significant free tier (1TB if you have a paid account, 100GB otherwise)

docs: https://huggingface.co/docs/hub/storage-limits

We optimize our infrastructure continuously to scale our storage for the coming years of growth in Machine learning, to the benefit of the community πŸ”₯

cc: @reach-vb @pierric @victor and the HF team
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reacted to cfahlgren1's post with πŸ‘πŸ”₯πŸš€ 2 months ago
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We just dropped an LLM inside the SQL Console 🀯

The amazing, new Qwen/Qwen2.5-Coder-32B-Instruct model can now write SQL for any Hugging Face dataset ✨

It's 2025, you shouldn't be hand writing SQL! This is a big step in making it where anyone can do in depth analysis on a dataset. Let us know what you think πŸ€—