FineWeb2: One Pipeline to Scale Them All -- Adapting Pre-Training Data Processing to Every Language
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2506.20920
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69
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YourBench: Easy Custom Evaluation Sets for Everyone
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2504.01833
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From Context to Action: Analysis of the Impact of State Representation and Context on the Generalization of Multi-Turn Web Navigation Agents
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2410.23555
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Better Slow than Sorry: Introducing Positive Friction for Reliable Dialogue Systems
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2501.17348
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ToolRL: Reward is All Tool Learning Needs
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2504.13958
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TD-EVAL: Revisiting Task-Oriented Dialogue Evaluation by Combining Turn-Level Precision with Dialogue-Level Comparisons
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2504.19982
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Language Specific Knowledge: Do Models Know Better in X than in English?
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2505.14990
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1
PIPA: A Unified Evaluation Protocol for Diagnosing Interactive Planning Agents
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2505.01592
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clefourrier
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Always surprised that so few people actually read the FineTasks blog, on
✨how to select training evals with the highest signal✨
If you're serious about training models without wasting compute on shitty runs, you absolutely should read it!!
An high signal eval actually tells you precisely, during training, how wel & what your model is learning, allowing you to discard the bad runs/bad samplings/...!
The blog covers in depth prompt choice, metrics, dataset, across languages/capabilities, and my fave section is "which properties should evals have"👌
(to know on your use case how to select the best evals for you)
Blog: HuggingFaceFW/blogpost-fine-tasks
✨how to select training evals with the highest signal✨
If you're serious about training models without wasting compute on shitty runs, you absolutely should read it!!
An high signal eval actually tells you precisely, during training, how wel & what your model is learning, allowing you to discard the bad runs/bad samplings/...!
The blog covers in depth prompt choice, metrics, dataset, across languages/capabilities, and my fave section is "which properties should evals have"👌
(to know on your use case how to select the best evals for you)
Blog: HuggingFaceFW/blogpost-fine-tasks
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- 2 replies
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6425
If you've followed the progress of robotics in the past 18 months, you've likely noticed how robotics is increasingly becoming the next frontier that AI will unlock.
At Hugging Face—in robotics and across all AI fields—we believe in a future where AI and robots are open-source, transparent, and affordable; community-built and safe; hackable and fun. We've had so much mutual understanding and passion working with the Pollen Robotics team over the past year that we decided to join forces!
You can already find our open-source humanoid robot platform Reachy 2 on the Pollen website and the Pollen community and people here on the hub at
pollen-robotics
We're so excited to build and share more open-source robots with the world in the coming months!
At Hugging Face—in robotics and across all AI fields—we believe in a future where AI and robots are open-source, transparent, and affordable; community-built and safe; hackable and fun. We've had so much mutual understanding and passion working with the Pollen Robotics team over the past year that we decided to join forces!
You can already find our open-source humanoid robot platform Reachy 2 on the Pollen website and the Pollen community and people here on the hub at
pollen-robotics
We're so excited to build and share more open-source robots with the world in the coming months!
- 1 reply
thomwolf
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lvwerra
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thomwolf
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dilekht
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Language Model is All You Need: Natural Language Understanding as Question Answering
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2011.03023
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Using In-Context Learning to Improve Dialogue Safety
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2302.00871
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1
VISITRON: Visual Semantics-Aligned Interactively Trained Object-Navigator
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2105.11589
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Simulating User Agents for Embodied Conversational-AI
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2410.23535
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1