Upload app.py

app.py

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+import gradio as gr
+import random
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+model_name = 'MR1B4RR4/Spanish_lyrics_model'
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
+
+def poema(text, num_lines):
+  num_lines=num_lines
+  poem = text
+  prev_output = ''
+
+  for i in range(num_lines):
+
+    input_text = f"""{poem}"""
+    inputs = tokenizer(input_text, return_tensors="pt")
+
+    outputs = model.generate(inputs["input_ids"],
+                            do_sample = True,
+                            max_length = 30,
+                            repetition_penalty = 20.0,
+                            top_k = 50,
+                            top_p = 0.92)
+    detok_outputs = [tokenizer.decode(x, skip_special_tokens=True) for x in outputs]
+    pre_output = detok_outputs[0]
+
+    poem += '\n' + pre_output
+  return poem
+  
+
+iface = gr.Interface(
+    fn=poema, 
+    title='Generation of Spanish poems',
+    description="""
+
+    Descripcion........
+    """,
+    theme='huggingface',
+    inputs=
+    [
+     gr.inputs.Textbox(lines=4, placeholder='texto inicial', label='Texto inicial'),
+     gr.inputs.Textbox(lines=4, placeholder='Numero de lineas', label='Numero de lineas')
+     ],
+     outputs=
+     [
+      gr.outputs.Textbox(label="Texto generado"),
+      # gr.outputs.Audio(label="Primeros segundos")
+      ])
+iface.launch(enable_queue=True)