Update app.py

app.py

@@ -1,30 +1,22 @@
 import gradio as gr
+from gradio import Textbox, Slider
 from transformers import GPT2LMHeadModel, GPT2Tokenizer
-import torch
 
 # Initialisierung des Modells und des Tokenizers
-tokenizer = GPT2Tokenizer.from_pretrained("Loewolf/GPT_1")
-model = GPT2LMHeadModel.from_pretrained("Loewolf/GPT_1")
+tokenizer = GPT2Tokenizer.from_pretrained("gpt2")
+model = GPT2LMHeadModel.from_pretrained("gpt2")
 
 def generate_text(prompt, max_length, temperature, top_k, top_p):
-    inputs = tokenizer.encode(prompt, return_tensors="pt")
-    outputs = model.generate(inputs, 
-                             max_length=max_length, 
-                             temperature=temperature, 
-                             top_k=top_k, 
-                             top_p=top_p, 
-                             num_return_sequences=1)
-    text = tokenizer.decode(outputs[0], skip_special_tokens=True)
-    return text
+    # [Ihr Code zur Textgenerierung hier]
 
 iface = gr.Interface(
     fn=generate_text, 
     inputs=[
-        gr.inputs.Textbox(lines=2, placeholder="Geben Sie einen Prompt ein..."), 
-        gr.inputs.Slider(minimum=10, maximum=100, default=50, label="Maximale Länge"),
-        gr.inputs.Slider(minimum=0.1, maximum=1.0, step=0.1, default=0.7, label="Temperatur"),
-        gr.inputs.Slider(minimum=0, maximum=50, default=20, label="Top K"),
-        gr.inputs.Slider(minimum=0.0, maximum=1.0, step=0.1, default=0.9, label="Top P")
+        Textbox(lines=2, placeholder="Geben Sie einen Prompt ein..."), 
+        Slider(minimum=10, maximum=100, default=50, label="Maximale Länge"),
+        Slider(minimum=0.1, maximum=1.0, step=0.1, default=0.7, label="Temperatur"),
+        Slider(minimum=0, maximum=50, default=20, label="Top K"),
+        Slider(minimum=0.0, maximum=1.0, step=0.1, default=0.9, label="Top P")
     ],
     outputs="text"
 )