import gradio as gr import requests import os import torch as th from torch import autocast from diffusers import StableDiffusionPipeline HF_TOKEN = os.environ["HF_TOKEN"] #HF_TOKEN = os.environ.get("diffuse_new") or True has_cuda = th.cuda.is_available() device = th.device('cpu' if not th.cuda.is_available() else 'cuda') print(f"device is :{device}") # init stable diffusion model pipe = StableDiffusionPipeline.from_pretrained( "CompVis/stable-diffusion-v1-4", use_auth_token= HF_TOKEN).to(device) def get_sd(translated_txt): scale=7.5 steps=45 with autocast('cpu' if not th.cuda.is_available() else 'cuda'): image = pipe(translated_txt, guidance_scale=scale, num_inference_steps=steps)["sample"][0] return image #API_URL = "https://api-inference.huggingface.co/models/bigscience/bloom" #HF_TOKEN = os.environ.get("diffuse_new") or True #headers = {"Authorization": f"Bearer {HF_TOKEN}"} sd_inf = gr.Blocks.load(name="spaces/stabilityai/stable-diffusion", use_auth_token=HF_TOKEN )#'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') def get_sd_old(translated_txt): print("******** Inside get_SD ********") print(f"translated_txt is : {translated_txt}") #sd_inf = gr.Blocks.load(name="spaces/stabilityai/stable-diffusion", use_auth_token='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') print(f"stable Diff inf is : {sd_inf}") sd_img_gallery = sd_inf(translated_txt, 4,45, 7.5,1024, fn_index=1 ) #(prompt, samples, steps, scale, seed) #translated_txt return sd_img_gallery[0] demo = gr.Blocks() with demo: gr.Markdown("Testing Diffusion models. STILL VERY MUCH WORK IN PROGRESS !!!!!!!!") with gr.Row(): in_text_prompt = gr.Textbox(label="Enter English text here") #out_text_chinese = gr.Textbox(label="Your Chinese language output") b1 = gr.Button("Generate SD") out_sd = gr.Image(type="pil", label="SD output for the given prompt") b1.click(get_sd, in_text_prompt, out_sd) #out_gallery ) demo.launch(enable_queue=True, debug=True)