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AI Models 84759

• princeton-nlp_-_Llama-3-Instruct-8B-SimPO-v0.2-gguf↗

  RichardErkhov

• stabilityai_-_japanese-stablelm-base-beta-70b-gguf↗

  RichardErkhov

• claude-oss-350m↗

  squ11z1

• Qwen3-0.6B-Code-Expert↗

  suayptalha

• SwarmDo-A1-GGUF↗

  SwarmDo

• plapre-nano-v2↗

  syvai

• DeepSeek-V4.1-Flash-MLX-2bit-MTP↗

  TensorFold

• CodeUp-Alpha-13B-HF-GGUF↗

  TheBloke

• stanford-car-vit-patch16↗

  therealcyberlord

  This achieves around 86% on the testing set, you can use it as a baseline for further tuning. The Stanford car dataset contains 16,185 images of 196 classes of cars. Classes are typically at the level of Make, Model, Year, e.g. 2012 Tesla Model S or 2012 BMW M3 coupe. The data is split into 8144 training images, 6,041 testing images, and 2000 validation images in this case. 3D Object Representations for Fine-Grained Categorization Jonathan Krause, Michael Stark, Jia Deng, Li Fei-Fei 4th IEEE Workshop on 3D Representation and Recognition, at ICCV 2013 (3dRR-13). Sydney, Australia. Dec. 8, 2013.

• controlnet-sd21↗

  thibaud

  Here's the first version of controlnet for stablediffusion 2.1 Trained on a subset of laion/laion-art You can use it with annotator depth/le_res but it works better with ZoeDepth Annotator. My PR is not accepted yet but you can use my fork. My fork: https://github.com/thibaudart/sd-webui-controlnet The PR: https://github.com/Mikubill/sd-webui-controlnet/pull/655#issuecomment-1481724024 The model should not be used to intentionally create or disseminate images that create hostile or alienating environments for people. This includes generating images that people would foreseeably find disturbing, distressing, or offensive; or content that propagates historical or current stereotypes.