Create app.py

app.py

@@ -0,0 +1,19 @@
+# Import the libraries
+import gradio as gr
+import transformers
+from transformers import GPT2Tokenizer, GPT2LMHeadModel
+
+# Load the tokenizer and model
+tokenizer = GPT2Tokenizer.from_pretrained('DarwinAnim8or/gpt-grug-1.5b')
+model = GPT2LMHeadModel.from_pretrained('DarwinAnim8or/gpt-grug-1.5b')
+
+# Define the function that generates text from a prompt
+def generate_text(prompt):
+  input_ids = tokenizer.encode(prompt, return_tensors='pt')
+  output = model.generate(input_ids, max_length=80, do_sample=True)
+  text = tokenizer.decode(output[0], skip_special_tokens=True)
+  return text
+
+# Create a gradio interface with a text input and a text output
+interface = gr.Interface(fn=generate_text, inputs='text', outputs='text')
+interface.launch()