Create app.py

app.py

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+import gradio as gr
+from transformers import pipeline, AutoModelForCausalLM, AutoTokenizer
+
+# Load the model and tokenizer from the repository
+model_name = "Dumele/autotrain-shhsb-57a2l"
+model = AutoModelForCausalLM.from_pretrained(model_name, trust_remote_code=True)
+tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
+
+# Define the text generation function
+def generate_text(prompt):
+    pipe = pipeline(task="text-generation", model=model, tokenizer=tokenizer, max_length=200)
+    result = pipe(prompt)
+    return result[0]['generated_text']
+
+# Create the Gradio interface
+iface = gr.Interface(
+    fn=generate_text,
+    inputs=gr.inputs.Textbox(lines=2, placeholder="Enter your prompt here..."),
+    outputs="text",
+    title="Text Generation with Mistral-7B",
+    description="Generate text using the fine-tuned Mistral-7B model from the Dumele repository."
+)
+
+# Launch the Gradio interface
+iface.launch()