undo sd3

app.py

@@ -6,13 +6,6 @@ import spaces
 import os
 import uuid
 from pydub import AudioSegment
-import numpy as np
-import random
-import torch
-from diffusers import StableDiffusion3Pipeline, SD3Transformer2DModel, FlowMatchEulerDiscreteScheduler
-
-
-'''AUDIO'''
 
 # Importing the model-related functions
 from stable_audio_tools import get_pretrained_model
@@ -97,37 +90,6 @@ def generate_audio(prompt, seconds_total=30, steps=100, cfg_scale=7):
     # Return the path to the generated audio file
     return full_path_mp3
 
-'''DIFFUSION'''
-device = "cuda" if torch.cuda.is_available() else "cpu"
-dtype = torch.float16
-
-repo = "stabilityai/stable-diffusion-3-medium-diffusers"
-pipe = StableDiffusion3Pipeline.from_pretrained(repo, torch_dtype=torch.float16).to(device)
-
-MAX_SEED = np.iinfo(np.int32).max
-MAX_IMAGE_SIZE = 1344
-
-@spaces.GPU
-def infer(prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps, progress=gr.Progress(track_tqdm=True)):
-
-    if randomize_seed:
-        seed = random.randint(0, MAX_SEED)
-        
-    generator = torch.Generator().manual_seed(seed)
-    
-    image = pipe(
-        prompt = prompt, 
-        negative_prompt = negative_prompt,
-        guidance_scale = guidance_scale, 
-        num_inference_steps = num_inference_steps, 
-        width = width, 
-        height = height,
-        generator = generator
-    ).images[0] 
-    
-    return image, seed
-
-'''
 # Setting up the Gradio Interface
 interface = gr.Interface(
     fn=generate_audio,
@@ -140,80 +102,9 @@ interface = gr.Interface(
     outputs=gr.Audio(type="filepath", label="Generated Audio"),
     title="Stable Audio Generator",
     description="Generate variable-length stereo audio at 44.1kHz from text prompts using Stable Audio Open 1.0.",
-)'''
-
-with gr.Blocks() as demo:
-    with gr.Tab("SD3"):
-        with gr.Column:
-            gr.Markdown(f"""
-            # Demo [Stable Diffusion 3 Medium](https://huggingface.co/stabilityai/stable-diffusion-3-medium)
-            Learn more about the [Stable Diffusion 3 series](https://stability.ai/news/stable-diffusion-3). Try on [Stability AI API](https://platform.stability.ai/docs/api-reference#tag/Generate/paths/~1v2beta~1stable-image~1generate~1sd3/post), [Stable Assistant](https://stability.ai/stable-assistant), or on Discord via [Stable Artisan](https://stability.ai/stable-artisan). Run locally with [ComfyUI](https://github.com/comfyanonymous/ComfyUI) or [diffusers](https://github.com/huggingface/diffusers)
-            """)
-        with gr.Row():
-            prompt = gr.Text(
-                label="Prompt",
-                show_label=False,
-                max_lines=1,
-                placeholder="Enter your prompt",
-                container=False,
-            )
-            run_button = gr.Button("Run", scale=0)
-        result = gr.Image(label="Result", show_label=False)
-
-        with gr.Accordion("Advanced Settings", open=False):
-            
-            negative_prompt = gr.Text(
-                label="Negative prompt",
-                max_lines=1,
-                placeholder="Enter a negative prompt",
-            )
-            
-            seed = gr.Slider(
-                label="Seed",
-                minimum=0,
-                maximum=MAX_SEED,
-                step=1,
-                value=0,
-            )
-            
-            randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
-            
-            with gr.Row():
-                
-                width = gr.Slider(
-                    label="Width",
-                    minimum=256,
-                    maximum=MAX_IMAGE_SIZE,
-                    step=64,
-                    value=1024,
-                )
-                
-                height = gr.Slider(
-                    label="Height",
-                    minimum=256,
-                    maximum=MAX_IMAGE_SIZE,
-                    step=64,
-                    value=1024,
-                )
-            
-            with gr.Row():
-                
-                guidance_scale = gr.Slider(
-                    label="Guidance scale",
-                    minimum=0.0,
-                    maximum=10.0,
-                    step=0.1,
-                    value=5.0,
-                )
-                
-                num_inference_steps = gr.Slider(
-                    label="Number of inference steps",
-                    minimum=1,
-                    maximum=50,
-                    step=1,
-                    value=28,
-                )
+)
 
+with gr.Blocks() as demo:                
     with gr.Tab("Audio"):
         audio_prompt =  gr.Textbox(label="Prompt", placeholder="Enter your text prompt here")
         audio_duration = gr.Slider(0, 47, value=30, label="Duration in Seconds")
@@ -223,12 +114,6 @@ with gr.Blocks() as demo:
         audio_output = gr.Audio(type="filepath", label="Generated Audio")
     audio_process_button.click(generate_audio, [audio_prompt, audio_duration, audio_steps, audio_cfg], [audio_output])
 
-    gr.on(
-        triggers=[run_button.click, prompt.submit, negative_prompt.submit],
-        fn = infer,
-        inputs = [prompt, negative_prompt, seed, randomize_seed, width, height, guidance_scale, num_inference_steps],
-        outputs = [result, seed]
-    )
 # Pre-load the model to avoid multiprocessing issues
 model, model_config = load_model()
 

requirements.txt

@@ -1,7 +1,3 @@
-git+https://github.com/huggingface/diffusers.git@sd3
-git+https://github.com/huggingface/transformers
-sentencepiece
-peft
 gradio
 Pillow
 requests