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We will release our code on a companion link:\nhttps://github
from the top result below
https://huggingface.co/papers?q=companion
We will release our code on a companion link:\nhttps://github
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
https://huggingface.co/datasets/teknium/OpenHermes-2.5
Consumption Function":5,"Opportunity/Alternative/ Transfer Cost":4,"Meaning of Price Elasticity of Demand":3,"Why does the Law of Demand Operate
https://huggingface.co/papers?q=reflective%20essays
","upvotes":3,"discussionId":"6679affcf926ce3cf48fd0d1","githubRepo":"https://github
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
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)
https://huggingface.co/koboldcpp
You can
do so by downloading
it from the <a href=\"https://
githubhttps://huggingface.co/papers/trending
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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
https://huggingface.co/papers?q=role-play
Hugging Face
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