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AI 模型 84760

• pegasus-xsum↗

  Google

  See Docs: here Authors: Jingqing Zhang, Yao Zhao, Mohammad Saleh and Peter J. Liu on Dec 18, 2019 We train a pegasus model with sampled gap sentence ratios on both C4 and HugeNews, and stochastically sample important sentences. The updated the results are reported in this table.

• gemma3-27b-cpt-gotoai-v3-instruct↗

  GoToCompany

• qwen35-trading-tool-agent-merged-GGUF↗

  GTKING

• h2o-lightning-4b-gguf↗

  h2oai

  GGUF files of H2O-Lightning-4B for llama.cpp. For the model description, training and general benchmarks, see the model page. Requests with images use a temperature of 1.0, set in the native files' metadata (the `stock-` path reads it from the shim's configuration). The model answers typed decisions with probabilities: named `choice` options, true/false `noul`, ordered `score` levels, and `box` (a bounding box in an image).

• HelpingAI2-6B↗

  HelpingAI

• Huihui-Qwen3-1.7B-abliterated-v2↗

  huihui-ai

• ThinkSafe-Qwen3-0.6B↗

  icml2026-7516

  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

• gemma-2-2b-it-abliterated↗

  IlyaGusev

• Sage-A1.5-APEX-I-NanoPlus-V2.1-GGUF↗

  IsValorum

• LTX-2.5-22b-IC-LoRA-Alpha-Gen↗

  Jacob121294