Delete app.py

app.py

@@ -1,54 +0,0 @@
-import gradio as gr
-import random
-from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
-
-model_name = 'MR1B4RR4/Spanish_lyrics_generator'
-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='texto inicial', label='Texto inicial')
-     ],
-     outputs=
-     [
-      gr.outputs.Textbox(label="Texto generado"),
-      # gr.outputs.Audio(label="Primeros segundos")
-      ],
-     examples=
-     [
-      ['Pablo Neruda', 'positivo', 'cielo, luna, mar', 'Todos fueron a verle pasar']
-     ])
-iface.launch(enable_queue=True)