MiniMax-H3
Aun1236基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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Raj-1.7B
aungzaythant基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗m2m100-418M-ct2-int8
auralmira基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗clip-ViT-B-32-multilingual-v1
aurantium基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗AURA
aurateam基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗OpenDDE
aurekaresearchOpenDDE is an open-source, all-atom biomolecular foundation model that turns co-folding into a scalable engine for structure prediction, design, and optimization in drug discovery. > [!IMPORTANT] > OpenDDE is a preview release. CLI flags, input/output JSON fields, and released > checkpoints may change between versions, and predictions are not guaranteed to > be reproducible across releases. It is not yet intended for production > pipelines. Please open an issue for bugs, regressions, or feature requests. OpenDDE requires Python `>=3.11`. The package pins PyTorch, so install with `uv` and choose the matching PyTorch backend explicitly.
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View details ↗sr-test-clip
aurelio-ai基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗sr-test-vit
aurelio-ai基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗matpac_music
auriankelen基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗Aurora1.0-150M
AuroraAI-Research基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗AuroraASR-1M
AuroraAI-Research基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗AuroraTTS-100K
AuroraAI-Research基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗qianwen3-14b-gguf
aurorac888基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗GLM-4.5-Air-iq4nl-GGUF
auRose94基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗GLM-4.5-Air-ninths-k63-e99-GGUF
auRose94基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗llama-30b-supercot
ausboss基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗chess-gpt2-uci-12x12x768
austindavis基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗Clover-35B-A3B-Preview-GGUF-IQ4_XS-Mac
austindixson基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗TaoMate-H3-FL2VA-ComfyUI
austinit基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗authormist-originality
authormist基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗Huihui-Qwen3.8-27B-abliterated-mlx-4Bit
AutisticAF基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗//////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////// Published by request from the Pennyroyal community. This is a ModelOpt NVFP4 conversion of OrcaRouter’s uncensored Qwen3.8 Flash-Next checkpoint—the conversion I use for local agentic work with Pennyroyal/SGLang. I’ve also heard reports from several community members of it outperforming the stock model on agentic tasks, which added to the interest in sharing this working format.
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View details ↗crp-safety-deberta-v1
AutoCyberAI基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗chronos-2
autogluon**Update Jun 5, 2026:** ☁️ Deploy Chronos-2 on AWS with AutoGluon-Cloud. Real-time, serverless, or batch inference in 3 lines of code — pandas DataFrames in, forecasts out. Check out the new deployment guide. **Chronos-2** is a 120M-parameter, encoder-only time series foundation model for zero-shot forecasting. It supports **univariate**, **multivariate**, and **covariate-informed** tasks within a single architecture. Inspired by the T5 encoder, Chronos-2 produces multi-step-ahead quantile forecasts and uses a group attention mechanism for efficient in-context learning across related series and covariates. Trained on a combination of real-world and large-scale synthetic datasets, it achieves **state-of-the-art zero-shot accuracy** among public models on **fev-bench**, **GIFT-Eval**, and **Chronos Benchmark II**. Chronos-2 is also **highly efficient**, delivering over 300 time series forecasts per second on a single A10G GPU and supporting both **GPU and CPU inference**. 🧩 Chronos & Chronos-Bolt do not natively support future covariates, but they can be combined with external covariate regressors (see AutoGluon tutorial). This only models per-timestep effects, not effects across time. In contrast, Chronos-2 supports all covariate types natively.
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