Create app.py

app.py

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+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM
+from huggingface_hub import login
+import os
+
+# Retrieve the Hugging Face token from the Space secrets
+token = os.getenv("HF_TOKEN")
+
+# Log in using the token
+login(token=token)
+
+
+# Load model and tokenizer
+model_name = "openai-community/gpt2"  #"meta-llama/Llama-3.2-3B"  # Replace with the correct model name if necessary
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+# Define inference function
+def generate_text(input_text):
+    inputs = tokenizer(input_text, return_tensors="pt")
+    outputs = model.generate(inputs["input_ids"], max_length=50, num_return_sequences=1)
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return response
+
+# Create Gradio interface
+iface = gr.Interface(fn=generate_text, inputs="text", outputs="text")
+
+# Launch the interface
+iface.launch()