best abliterated uncensored models on hugging face that support vision

As of my last update in October 2023, Hugging Face hosts a variety of models that can handle vision tasks. For "abliterated" models, it seems like you may be referring to models that have been fine-tuned or specialized for certain tasks, but the specific term "abliterated" isn’t standard in the context of model descriptions. However, if you are looking for state-of-the-art vision models that are uncensored or capable of interpreting and generating images, here are some popular categories available on Hugging Face: 1. **Vision Transformers (ViT)**: - ViT models are popular for image classification tasks. Look for variants fine-tuned on specific datasets. 2. **DALL-E & Stable Diffusion**: - These models are notable for generating images from text prompts. They are widely used for creative generative tasks and can handle uncensored prompts, depending on the implementation. 3. **CLIP (Contrastive Language-Image Pretraining)**: - CLIP models can understand and relate text and images, allowing for diverse applications in vision and language tasks. 4. **YOLO (You Only Look Once)**: - These models are designed for object detection tasks and are available in various versions on Hugging Face. 5. **Detectron2**: - A model framework that provides state-of-the-art detection algorithms. 6. **OpenVINO Models**: - Models optimized for inference performance and might also be adapted for various vision tasks. To explore and find the most suitable uncensored models, you can visit the [Hugging Face Model Hub](https://huggingface.co/models) and filter by tasks such as "Image Classification", "Object Detection", "Generative Models", and others. Make sure to review the licensing and use case limitations indicated for each model, as these can vary. If you have specific vision tasks or applications in mind, please provide further details, and I’d be happy to help narrow down options!