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10 result(s) for “okapi bm25 site hotchips pp site github com site vi do union it site:huggingface.co” · 705 ms
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Freshness: newest result fetched 24 d ago · median age of these results 24 d · 1 of 10 carry a fetch time
Lastly, it's important to note that the selected models do prioritise user privacy by allowing users to delete their own conducted conversations
from the top result below
https://huggingface.co/papers?q=reflective%20essays
","upvotes":3,"discussionId":"6679affcf926ce3cf48fd0d1","githubRepo":"https://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/koboldcpp
You can do so by downloading it from the <a href=\"https://github
https://huggingface.co/papers?q=companion
It is\nfound that the lower limit of binarity is 30
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/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/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
https://huggingface.co/docs/hub/repositories-github-actions
The official huggingface/hub-sync action supports syncing Models, Datasets, and Spaces
https://huggingface.co/papers?q=role-play
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https://huggingface.co/papers/trending
8T scale, Kimi K3 is supported by infrastructure advances in multiple areas: algorithm-system co-design for KDA, perfectly balanced expert-parallel training with efficient memory management, million-token agentic RL with persistent rollout and sandbox states, and deployment innovations