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app.py

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+from diffusers import StableDiffusionPipeline,  EulerDiscreteScheduler
+from transformers import pipeline
+import torch
+from IPython.display import clear_output
+import gradio as gr
+
+model_name = "stabilityai/stable-diffusion-2"
+scheduler = EulerDiscreteScheduler.from_pretrained(model_name, subfolder="scheduler")
+pipe = StableDiffusionPipeline.from_pretrained(model_name, scheduler=scheduler, revision="fp16", torch_dtype=torch.float16)
+
+# Movemos el pipeline a GPU para tener una inferencia más rápida.
+device = "cuda" if torch.cuda.is_available() else "cpu"
+pipe = pipe.to(device)
+pipe.enable_attention_slicing() 
+
+# Cargamos el modelo traductor y creamos el pipeline para traducir al ingles
+spanish_model_name = "Helsinki-NLP/opus-mt-es-en"
+translator_es_en = pipeline("translation", model=spanish_model_name)
+
+def predict(text):
+  prompt_es = text
+  english_text = translator_es_en(prompt_es)
+  prompt_en = english_text[0]['translation_text']
+  image = pipe(prompt_en).images[0]
+  return image
+
+description = """
+<h2 style="text-align:center">Programa para generar imágenes a partir de texto con Stable Diffusion 2</h2>
+<h2 style="text-align:center">Prompt en español!!</h2>
+"""
+
+gr.Interface(fn=predict,
+              title="Texto a Imagen en Español",
+              inputs= gr.Textbox("", max_lines = 2, label = "Inserte su texto aqui"),
+              outputs = "image",
+              description = description).launch(debug=True)

requirements.txt

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+transformers
+gradio
+torch
+sacremoses==0.0.53
+sentencepiece==0.1.97
+accelerate 
+scipy
+diffusers @ git+https://github.com/huggingface/diffusers.git