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app.py

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+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+model_name = "deepseek-ai/deepseek-coder-1.3b-base"
+
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(
+    model_name,
+    torch_dtype=torch.float16,
+    device_map="auto"
+)
+
+def generate_code(prompt):
+    inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
+    outputs = model.generate(**inputs, max_new_tokens=300, pad_token_id=tokenizer.eos_token_id)
+    return tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+examples = [
+    "Write a Python function to calculate the factorial of a number.",
+    "Generate a React component for a simple to-do list.",
+    "Create a SQL query to find the top 5 selling products.",
+    "Write a JavaScript function to validate email addresses.",
+    "Generate a CSS style for a responsive navbar."
+]
+
+with gr.Blocks() as demo:
+    gr.Markdown("## 💻 DeepSeek Code Generator")
+    prompt = gr.Textbox(label="Enter your code description here", lines=3)
+    output = gr.Textbox(label="Generated Code", lines=15)
+    generate_btn = gr.Button("Generate Code")
+    examples_box = gr.Column(visible=False)
+    toggle_examples_btn = gr.Button("Show Examples")
+
+    def generate_click(prompt_text):
+        return generate_code(prompt_text)
+
+    def toggle_examples():
+        return gr.update(visible=not examples_box.visible)
+
+    generate_btn.click(fn=generate_click, inputs=prompt, outputs=output)
+    toggle_examples_btn.click(fn=toggle_examples, inputs=None, outputs=examples_box)
+
+    with examples_box:
+        for ex in examples:
+            ex_btn = gr.Button(ex, variant="secondary", size="sm")
+            ex_btn.click(fn=lambda x=ex: x, inputs=None, outputs=prompt)
+
+demo.launch()
+

requirements.txt

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+transformers
+torch
+gradio
+