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amenur

amenur

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upvoted an article 6 days ago

Welcome Llama 4 Maverick & Scout on Hugging Face!

liked a model 29 days ago

sesame/csm-1b

upvoted an article about 1 month ago

SmolVLM2: Bringing Video Understanding to Every Device

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upvoted an article 6 days ago

Article

Welcome Llama 4 Maverick & Scout on Hugging Face!

7 days ago

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liked a model 29 days ago

sesame/csm-1b

Text-to-Speech • Updated 26 days ago • 93k • • 1.84k

upvoted an article about 1 month ago

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SmolVLM2: Bringing Video Understanding to Every Device

Feb 20

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upvoted 2 articles about 2 months ago

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SigLIP 2: A better multilingual vision language encoder

Feb 21

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Open-source DeepResearch – Freeing our search agents

Feb 4

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upvoted 2 articles 2 months ago

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Introducing smolagents: simple agents that write actions in code.

Dec 31, 2024

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Open-R1: a fully open reproduction of DeepSeek-R1

Jan 28

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upvoted a paper 4 months ago

Qwen2.5 Technical Report

Paper • 2412.15115 • Published Dec 19, 2024 • 365

upvoted a collection 4 months ago

Scaling Test-Time Compute with Open Models

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Models and datasets used in our blog post: https://huggingface.co/spaces/HuggingFaceH4/blogpost-scaling-test-time-compute • 10 items • Updated Jan 6 • 23

liked a Space 4 months ago

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Scaling test-time compute

📈

Enhance math problem solving by scaling test-time compute

reacted to lewtun's post with 🚀🔥 4 months ago

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We outperform Llama 70B with Llama 3B on hard math by scaling test-time compute 🔥

How? By combining step-wise reward models with tree search algorithms :)

We show that smol models can match or exceed the performance of their much larger siblings when given enough "time to think"

We're open sourcing the full recipe and sharing a detailed blog post.

In our blog post we cover:

📈 Compute-optimal scaling: How we implemented DeepMind's recipe to boost the mathematical capabilities of open models at test-time.

🎄 Diverse Verifier Tree Search (DVTS): An unpublished extension we developed to the verifier-guided tree search technique. This simple yet effective method improves diversity and delivers better performance, particularly at large test-time compute budgets.

🧭 Search and Learn: A lightweight toolkit for implementing search strategies with LLMs and built for speed with vLLM

Here's the links:

- Blog post: HuggingFaceH4/blogpost-scaling-test-time-compute

- Code: https://github.com/huggingface/search-and-learn

Enjoy!