class SD35Generator: def __init__( self, model, enable_quantize=False, enable_fast_transformer=False, enable_speedup_t5=False, + args=None, + device=None, ): + self.args = args + self.device = device or torch.device("cuda") self.pipe = StableDiffusion3Pipeline.from_pretrained( model...
name_or_path: "runwayml/stable-diffusion-v1-5" is_v2: false # for v2 models is_v_pred: false # for v-prediction models (most v2 models) # saving config save: dtype: float16 # precision to save. I recommend float16 save_every: 100 # save every this many steps # sampling config...
An iOS app that generates images from text prompts utilizing Stable Diffusion API 23 September 2023 macOS A macOS filetree generator built with SwiftUI A macOS filetree generator built with SwiftUI 11 July 2023 Stable Diffusion A macOS screensaver that generates abstract art using Stable Di...
Specifically, we adopt a text-to-image gener- ation model, Stable Diffusion [51], in consideration of two main reasons. First, it has a strong capability to generate high-quality in-the-wild images, thanks to the property that given any vector lying in its l...
Train an embedding or Hypernetwork; you must specify a directory with a set of 1:1 ratio images [wiki]") with gr.Row(): train_embedding_name = gr.Dropdown(label='Embedding', elem_id="train_embedding", choices=sorted(sd_hijack.model_hijack.embedding_db.word_embeddings.keys())) create_...
" \"engine\": \"stable-diffusion-xl-1024-v1-0\",\n", " \"prompts\": \"{ gpt.output.texts }\",\n", " \"style_preset\": \"comic-book\",\n", " \"width\": 896,\n", " \"height\": 1152,\n", " }\n", " },\n", " \"task\": \"TASK_TEXT_TO_IMAGE\",\n"...