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AI 모델 84760

• deberta-v3-large-tasksource-nli↗

  sileod

• A.X-K1↗

  skt

  **A.X K1** is a large-scale Mixture-of-Experts (MoE) language model designed for efficient high-capacity reasoning and instruction following, and was trained from scratch without initializing from an existing pretrained model. The model contains **519 billion total parameters**, with **33 billion active parameters**, enabling strong performance while maintaining practical inference efficiency. This hybrid design allows the user to choose between in-depth reasoning and response latency depending on task requirements. A.X K1 follows a sparse Mixture-of-Experts architecture in which only a subset of experts is activated per token. This design substantially increases model capacity while keeping the computational cost comparable to dense models with much smaller parameter counts.

• efficientnet-b6.imagenet↗

  smp-hub

• Huihui-Qwen3.8-27B-Swift1.5-Abliterated-IQ3S-DFlash2-NInfer↗

  SPK1337

  Community **conversion and component combination**, **not a newly trained model**. The NInfer v3 artifact combines the Huihui *abliterated Swift-1.5 GSQ-RCO IQ3_S* GGUF text weights (including MTP), a pretrained Qwen3.8-27B DFlash2 drafter, and the Qwen3.8-27B vision projector. > **RTX 4090 local benchmark (19 October 2026): up to 229.04 output tokens/s in a 2,048-token single-request decode test (32K input), 191.78 tokens/s at 160K input, and 63/63 successful HTTP requests.** These are *client-side measurements of the entire server*, not isolated DFlash2 speedups. See BENCHMARK.md for methodology and limits. This file is **not** a standard Transformers checkpoint and cannot be loaded directly with `transformers.AutoModel.from_pretrained`.

• maple-preview-gguf↗

  stamsam

• Gemmasutra-9B-v1.1-GGUF↗

  TheDrummer

• gemini_whisper_ipa↗

  thunderboltc

• eva02_large_patch14_clip_336.merged2b↗

  timm

• fastvit_ma36.apple_in1k↗

  timm

• mMiniLM-L6-v2-mmarco-v2↗

  unicamp-dl