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AI 모델 84999

• SN3810↗

  thieu86

• sundial-base-128m↗

  thuml

  🚩 **News (2025.08)** Sundial has been integrated into Apache IoTDB, a native time-series database. 🚩 **News (2025.05)** Get **1st MASE** on the GIFT-Eval Benchmark. 🚩 **News (2025.02)** Get **1st MSE/MAE** zero-shot performance on Time-Series-Library datasets.

• eca_nfnet_l1.ra2_in1k↗

  timm

• repvit_m1.dist_in1k↗

  timm

  A RepViT image classification model. Trained on ImageNet-1k with distillation by paper authors. - **Model Type:** Image classification / feature backbone - **Model Stats:** - Params (M): 5.5 - GMACs: 0.8 - Activations (M): 7.4 - Image size: 224 x 224 - **Papers:** - RepViT: Revisiting Mobile CNN From ViT Perspective: https://arxiv.org/abs/2307.09283 - **Original:** https://github.com/THU-MIG/RepViT - **Dataset:** ImageNet-1k

• FLUX.1-schnell-GGUF↗

  unsloth

  `FLUX.1 [schnell]` is a 12 billion parameter rectified flow transformer capable of generating images from text descriptions. For more information, please read our blog post. 1. Cutting-edge output quality and competitive prompt following, matching the performance of closed source alternatives. 2. Trained using latent adversarial diffusion distillation, `FLUX.1 [schnell]` can generate high-quality images in only 1 to 4 steps. 3. Released under the `apache-2.0` licence, the model can be used for personal, scientific, and commercial purposes. We provide a reference implementation of `FLUX.1 [schnell]`, as well as sampling code, in a dedicated github repository. Developers and creatives looking to build on top of `FLUX.1 [schnell]` are encouraged to use this as a starting point. The FLUX.1 models are also available via API from the following sources - bfl.ml (currently `FLUX.1 [pro]`) - replicate.com - fal.ai - mystic.ai `FLUX.1 [schnell]` is also available in Comfy UI for local inference with a node-based workflow. To use `FLUX.1 [schnell]` with the 🧨 diffusers python library, first install or upgrade diffusers To learn more check out the diffusers documentation --- - This model is not intended or able to provide factual information. - As a statistical model this checkpoint might amplify existing societal biases. - The model may fail to generate output that matches the prompts. - Prompt following is heavily influenced by the prompting-style.

• Phi-4-reasoning-GGUF↗

  unsloth

• VersaViT↗

  腾讯

• Sakura-Qwen-Image-2.1-Turbo-GGUF↗

  webmp3

• toxic-bert↗

  Xenova

  Note: Having a separate repo for ONNX weights is intended to be a temporary solution until WebML gains more traction. If you would like to make your models web-ready, we recommend converting to ONNX using 🤗 Optimum and structuring your repo like this one (with ONNX weights located in a subfolder named `onnx`).

• MiMo-Embodied-7B↗

  XiaomiMiMo