Create sample.py

sample.py

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+import os
+import gradio as gr
+from transformers import pipeline
+
+# Get the token from environment variables
+# token = os.getenv("HUGGINGFACE_TOKEN")
+# if token is None:
+#     raise ValueError("Hugging Face token is not set in the environment variables.")
+
+# Load the model from the Hugging Face Model Hub with authentication
+generator = pipeline('text-generation', model='your-model-name', use_auth_token=token)
+
+# Define the prediction function
+def generate_text(prompt):
+    result = generator(prompt, max_length=50)
+    return result[0]['generated_text']
+
+# Create the Gradio interface
+iface = gr.Interface(fn=generate_text, inputs="text", outputs="text")
+
+# Launch the app
+iface.launch()