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It\neffectively reduces the searching space of pairing and drives an implicit and\nsoft learning of negative pairs via a gradient
from the top result below

Daily Papers - Hugging Face

https://huggingface.co/papers?q=companion
It\neffectively reduces the searching space of pairing and drives an implicit and\nsoft learning of negative pairs via a gradient

microsoft/benchpress-score-matrix · Datasets at Hugging Face

https://huggingface.co/datasets/microsoft/benchpress-score-matrix
00933 defines the full MCP-Atlas benchmark as 1,000 tasks over 36 real MCP servers and 220 tools; the ScaleAI/MCP-Atlas HF card and scaleapi/mcp-atlas GitHub repo expose the public release as 500 evaluation prompts/tasks, matching this MCPAtlas Public benchmark row

2048 Token Examples":1,"Collaboration for Effective Communication.":1

https://huggingface.co/datasets/teknium/OpenHermes-2.5
,"Taco Seasoning Recipe":1,"Invite collaborator privately.":1,"提高自律能力":1,"Stinky Doge Coin Rap":1,"エクセル:文字列の結合 (Excel: Concatenating Strings)":1}}}},{"name":"topic","align":"right","type":"null","statistics

Daily Papers - Hugging Face

https://huggingface.co/papers?q=reflective%20essays
","upvotes":3,"discussionId":"6679affcf926ce3cf48fd0d1","githubRepo":"https://github

Daily Papers - Hugging Face

https://huggingface.co/papers?q=persona
Our findings reveal a critical trade-off: while PP can improve classification in socially-sensitive tasks, it often comes at the cost of rationale quality and fails to mitigate underlying biases, urging caution in its application

Daily Papers - Hugging Face

https://huggingface.co/papers?q=role-play
000Z","title":"Character Beyond Speech: Leveraging Role-Playing Evaluation in Audio Large Language Models via Reinforcement Learning","summary":"The rapid evolution of multimodal large models has revolutionized the simulation of diverse characters in speech dialogue systems, enabling a novel interactive paradigm

GitHub Actions · Hugging Face

https://huggingface.co/docs/hub/repositories-github-actions
For keyless publishing — no HF_TOKEN secret to store or rotate — see Trusted Publishers, which exchanges GitHub Actions’ built-in OIDC token for a short-lived, repo-scoped Hub token at the start of each run

koboldcpp (Koboldcpp)

https://huggingface.co/koboldcpp
You can do so by downloading it from the <a href=\"https://github

Trending Papers - Hugging Face

https://huggingface.co/papers/trending
Hugging Face Models Datasets Spaces Buckets new Docs Enterprise Pricing Website Tasks HuggingChat Collections Languages Organizations Community Blog Posts Daily Papers Hardware Learn Discord Forum GitHub Solutions Team

Storage limits · Hugging Face

https://huggingface.co/docs/hub/storage-limits
We do have mitigations in place to prevent abuse of free public storage, and in general we ask users and organizations to make sure any uploaded large model or dataset is as useful to the community as possible (as represented by numbers of likes or downloads, for instance)