Update app.py

app.py

@@ -1,25 +1,42 @@
 import gradio as gr
-from transformers import GPT2LMHeadModel, GPT2Tokenizer
-
-# Carregue o modelo GPT-2 pré-treinado e o tokenizador
-model_name = "gpt2"  # Pode ser substituído por outros modelos GPT-2 maiores
-tokenizer = GPT2Tokenizer.from_pretrained(model_name)
-model = GPT2LMHeadModel.from_pretrained(model_name)
-
-# Função para gerar respostas com base na entrada do usuário
-def chatbot(input_text):
-    input_ids = tokenizer.encode(input_text, return_tensors="pt")
-    response_ids = model.generate(input_ids, max_length=50, num_return_sequences=1)
-    response = tokenizer.decode(response_ids[0], skip_special_tokens=True)
-    return response
-
-# Interface Gradio para o chatbot
-iface = gr.Interface(
-    fn=chatbot,
-    inputs="text",
-    outputs="text",
-    title="Chatbot GPT-2",
-    description="Converse com o Chatbot GPT-2 usando texto.",
-)
-
-iface.launch()
+from gradio import mix
+
+title = "GPT2"
+description = "Gradio Demo for OpenAI GPT2. To use it, simply add your text, or click one of the examples to load them. Read more at the links below."
+
+article = "<p style='text-align: center'><a href='https://d4mucfpksywv.cloudfront.net/better-language-models/language_models_are_unsupervised_multitask_learners.pdf' target='_blank'>Language Models are Unsupervised Multitask Learners</a></p>"
+
+examples = [
+    ['Paris is the capital of',"gpt2-medium"]
+]
+
+io1 = gr.Interface.load("huggingface/distilgpt2")
+
+io2 = gr.Interface.load("huggingface/gpt2-large")
+
+io3 = gr.Interface.load("huggingface/gpt2-medium")
+
+io4 = gr.Interface.load("huggingface/gpt2-xl")
+
+def inference(text, model):
+    if model == "gpt2-large":
+        outtext = io2(text)
+    elif model == "gpt2-medium":
+        outtext = io3(text)
+    elif model == "gpt2-xl":
+        outtext = io4(text)
+    else:
+        outtext = io1(text)
+    return outtext   
+    
+     
+
+gr.Interface(
+    inference, 
+    [gr.inputs.Textbox(label="Input"),gr.inputs.Dropdown(choices=["distilgpt2","gpt2-medium","gpt2-large","gpt2-xl"], type="value", default="gpt2-medium", label="model")
+], 
+    gr.outputs.Textbox(label="Output"),
+    examples=examples,
+    article=article,
+    title=title,
+    description=description).launch(enable_queue=True)