Create app.py

app.py

@@ -0,0 +1,28 @@
+import gradio as gr
+import os
+os.system('pip install transformers')
+from transformers import AutoTokenizer, AutoModelWithLMHead
+
+# Load the tokenizer and model
+tokenizer = AutoTokenizer.from_pretrained("gpt2")
+model = AutoModelWithLMHead.from_pretrained("gpt-model-article")
+
+def greet(prompt,temperature,top_k,top_p,max_len):
+    
+    # Generate text using the fine-tuned model
+    input_ids = tokenizer.encode(prompt, return_tensors="pt")
+
+    # Generate the output
+    output = model.generate(
+        input_ids,
+        max_length=max_len,
+        do_sample=True,
+        temperature=temperature,
+        top_k=top_k,
+        top_p=top_p
+    )
+
+    return str(tokenizer.decode(output[0], skip_special_tokens=True))
+
+iface = gr.Interface(fn=greet, inputs=["text",gr.Slider(0, 1, 0.8),gr.Slider(0, 1, 0),gr.Slider(0, 1, 0.9),gr.Slider(0, 250, 100)], outputs="text")
+iface.launch()