Create app.py

app.py

@@ -0,0 +1,24 @@
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+# Load the tokenizer and model
+tokenizer = AutoTokenizer.from_pretrained("bigscience/bloom-560m")
+model = AutoModelForCausalLM.from_pretrained("bigscience/bloom-560m")
+
+# Define a function to generate text
+def generate_text(prompt):
+    input_ids = tokenizer.encode(prompt, return_tensors="pt")
+    output = model.generate(input_ids, max_length=100, num_return_sequences=1)
+    generated_text = tokenizer.decode(output[0], skip_special_tokens=True)
+    return generated_text
+
+# Create a Gradio interface
+interface = gr.Interface(
+    fn=generate_text,
+    inputs=gr.Textbox("text", label="Enter your prompt here:"),
+    outputs=gr.Textbox("text", label="Generated Text:")
+)
+
+# Launch the interface
+interface.launch()