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README.md

@@ -1,14 +1,17 @@
----
-title: ROSPRITE
-emoji: 🖼
-colorFrom: purple
-colorTo: red
-sdk: gradio
-sdk_version: 5.25.2
-app_file: app.py
-pinned: false
-license: apache-2.0
-short_description: space for CharaForge
----
+# Generador con SDXL + LoRA en GPU T4 Gratis
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+Este Space usa:
+- Modelo base: stabilityai/stable-diffusion-xl-base-1.0
+- LoRA de ejemplo: nerijs/pixel-art-xl
+
+## Cómo cambiar el LoRA
+1. Sube tu LoRA a Hugging Face (como modelo).
+2. En `app.py`, reemplaza:
+   LORA_MODEL = "nerijs/pixel-art-xl"
+   por tu repo: "usuario/mi-lora"
+3. Guarda y vuelve a lanzar el Space.
+
+## Recomendaciones para GPU T4
+- Usar `torch_dtype=torch.float16`
+- 20–30 pasos de inferencia
+- Mantener LoRAs livianos para evitar OOM

app.py

@@ -1,154 +1,35 @@
-import gradio as gr
-import numpy as np
-import random
-
-# import spaces #[uncomment to use ZeroGPU]
-from diffusers import DiffusionPipeline
 import torch
+from diffusers import StableDiffusionXLPipeline
+import gradio as gr
 
-device = "cuda" if torch.cuda.is_available() else "cpu"
-model_repo_id = "stabilityai/sdxl-turbo"  # Replace to the model you would like to use
-
-if torch.cuda.is_available():
-    torch_dtype = torch.float16
-else:
-    torch_dtype = torch.float32
-
-pipe = DiffusionPipeline.from_pretrained(model_repo_id, torch_dtype=torch_dtype)
-pipe = pipe.to(device)
-
-MAX_SEED = np.iinfo(np.int32).max
-MAX_IMAGE_SIZE = 1024
-
-
-# @spaces.GPU #[uncomment to use ZeroGPU]
-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
-
-
-examples = [
-    "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k",
-    "An astronaut riding a green horse",
-    "A delicious ceviche cheesecake slice",
-]
-
-css = """
-#col-container {
-    margin: 0 auto;
-    max-width: 640px;
-}
-"""
-
-with gr.Blocks(css=css) as demo:
-    with gr.Column(elem_id="col-container"):
-        gr.Markdown(" # Text-to-Image Gradio Template")
-
-        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, variant="primary")
-
-        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",
-                visible=False,
-            )
-
-            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=32,
-                    value=1024,  # Replace with defaults that work for your model
-                )
-
-                height = gr.Slider(
-                    label="Height",
-                    minimum=256,
-                    maximum=MAX_IMAGE_SIZE,
-                    step=32,
-                    value=1024,  # Replace with defaults that work for your model
-                )
-
-            with gr.Row():
-                guidance_scale = gr.Slider(
-                    label="Guidance scale",
-                    minimum=0.0,
-                    maximum=10.0,
-                    step=0.1,
-                    value=0.0,  # Replace with defaults that work for your model
-                )
-
-                num_inference_steps = gr.Slider(
-                    label="Number of inference steps",
-                    minimum=1,
-                    maximum=50,
-                    step=1,
-                    value=2,  # Replace with defaults that work for your model
-                )
-
-        gr.Examples(examples=examples, inputs=[prompt])
-    gr.on(
-        triggers=[run_button.click, prompt.submit],
-        fn=infer,
-        inputs=[
-            prompt,
-            negative_prompt,
-            seed,
-            randomize_seed,
-            width,
-            height,
-            guidance_scale,
-            num_inference_steps,
-        ],
-        outputs=[result, seed],
-    )
+# Modelo base
+BASE_MODEL = "stabilityai/stable-diffusion-xl-base-1.0"
+# LoRA de ejemplo (puedes cambiarlo por el tuyo)
+LORA_MODEL = "nerijs/pixel-art-xl"
+
+print("Cargando modelo base...")
+pipe = StableDiffusionXLPipeline.from_pretrained(
+    BASE_MODEL,
+    torch_dtype=torch.float16,
+    variant="fp16",
+    use_safetensors=True
+).to("cuda")
+
+print("Cargando LoRA...")
+pipe.load_lora_weights(LORA_MODEL)
+pipe.fuse_lora(lora_scale=0.8)  # Ajusta el peso del LoRA
+
+def generar(prompt):
+    with torch.inference_mode():
+        image = pipe(prompt, num_inference_steps=25).images[0]
+    return image
+
+demo = gr.Interface(
+    fn=generar,
+    inputs=gr.Textbox(label="Prompt", placeholder="Escribe tu prompt aquí..."),
+    outputs=gr.Image(label="Imagen generada"),
+    title="Generador con LoRA en T4 Gratis"
+)
 
 if __name__ == "__main__":
     demo.launch()

requirements.txt

@@ -1,6 +1,6 @@
+torch==2.3.1
+transformers>=4.40.0
+diffusers>=0.29.0
 accelerate
-diffusers
-invisible_watermark
-torch
-transformers
-xformers
+safetensors
+gradio>=4.0.0