Yahoo Poland Wyszukiwanie w Internecie

Search results

  1. stable-diffusion. like 10.5k. Running on CPU Upgrade. App Files Files Community 20002 Refreshing. Discover amazing ML apps made by the community Spaces. stabilityai / stable-diffusion. like 10.5k. Running on CPU Upgrade. App Files Files Community . 20002. Refreshing ...

    • Stable-diffusion-1

      Explore the amazing text-to-image generation with Stable...

    • Stabilityai

      Our vibrant communities consist of experts, leaders and...

  2. 12 cze 2024 · Stable Diffusion 3 Medium is a Multimodal Diffusion Transformer (MMDiT) text-to-image model that features greatly improved performance in image quality, typography, complex prompt understanding, and resource-efficiency.

  3. Stable Diffusion is a Latent Diffusion model developed by researchers from the Machine Vision and Learning group at LMU Munich, a.k.a CompVis. Model checkpoints were publicly released at the end of August 2022 by a collaboration of Stability AI, CompVis, and Runway with support from EleutherAI and LAION.

  4. 1 lis 2023 · HuggingFace Stable Diffusion XL is a multi-expert pipeline for latent diffusion. Initially, a base model produces preliminary latents, which are then refined by a specialized model (found here) that focuses on the final denoising. The base model is also functional independently.

  5. New stable diffusion finetune ( Stable unCLIP 2.1, Hugging Face) at 768x768 resolution, based on SD2.1-768. This model allows for image variations and mixing operations as described in Hierarchical Text-Conditional Image Generation with CLIP Latents, and, thanks to its modularity, can be combined with other models such as KARLO.

  6. 12 cze 2024 · Stable Diffusion 3 Medium is Stability AIs most advanced text-to-image open model yet. The small size of this model makes it perfect for running on consumer PCs and laptops as well as enterprise-tier GPUs. It is suitably sized to become the next standard in text-to-image models.

  7. 9 lis 2022 · The stable diffusion model takes the textual input and a seed. The textual input is then passed through the CLIP model to generate textual embedding of size 77x768 and the seed is used to generate Gaussian noise of size 4x64x64 which becomes the first latent image representation.

  1. Ludzie szukają również