Create app.py

app.py

@@ -0,0 +1,129 @@
+import gradio as gr
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+# Load model with optimization for free GPU
+model_name = "mistralai/Devstral-Small-2505"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+
+# Optimization for free GPU
+model = AutoModelForCausalLM.from_pretrained(
+    model_name,
+    torch_dtype=torch.float16,  # Use half precision
+    device_map="auto",          # Automatically distribute across available devices
+    load_in_8bit=True,          # 8-bit quantization to save memory
+)
+
+def generate_text(prompt, max_length=512, temperature=0.7, top_p=0.9):
+    inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
+    
+    with torch.no_grad():
+        outputs = model.generate(
+            inputs.input_ids,
+            max_length=max_length,
+            temperature=temperature,
+            top_p=top_p,
+            do_sample=True,
+            pad_token_id=tokenizer.eos_token_id
+        )
+    
+    response = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    return response
+
+# Custom CSS for a more beautiful interface
+custom_css = """
+.container {
+    max-width: 900px;
+    margin: auto;
+    padding-top: 1.5rem;
+}
+.title {
+    text-align: center;
+    color: #2a4365;
+}
+.subtitle {
+    text-align: center;
+    color: #4a5568;
+    margin-bottom: 2rem;
+}
+footer {display: none !important;}
+.gradio-container {
+    font-family: 'Inter', -apple-system, BlinkMacSystemFont, sans-serif;
+}
+.gr-button {
+    border-radius: 8px !important;
+}
+.gr-button.gr-button-lg {
+    padding: 8px 18px;
+}
+.gr-input, .gr-textarea {
+    border-radius: 8px !important;
+}
+.gr-form {
+    border-radius: 12px !important;
+    padding: 20px !important;
+    background: #f8fafc !important;
+}
+.advanced-options {
+    margin-top: 1rem;
+    padding: 1rem;
+    border-radius: 8px;
+    background: #edf2f7;
+}
+"""
+
+# Create enhanced minimalist interface
+with gr.Blocks(css=custom_css) as demo:
+    with gr.Column(elem_classes="container"):
+        gr.Markdown("# Devstral-Small-2505 Demo", elem_classes="title")
+        gr.Markdown("Experience the power of Mistral's latest code-focused model", elem_classes="subtitle")
+        
+        with gr.Box():
+            prompt = gr.Textbox(
+                placeholder="Enter your prompt here...", 
+                label="Input",
+                lines=5
+            )
+            
+            with gr.Row():
+                submit_btn = gr.Button("Generate", variant="primary", scale=2)
+                clear_btn = gr.Button("Clear", scale=1)
+            
+            with gr.Accordion("Advanced Options", open=False):
+                with gr.Row():
+                    with gr.Column():
+                        max_length = gr.Slider(
+                            minimum=64, maximum=2048, value=512, step=64,
+                            label="Maximum Length"
+                        )
+                    with gr.Column():
+                        temperature = gr.Slider(
+                            minimum=0.1, maximum=1.0, value=0.7, step=0.1,
+                            label="Temperature (Creativity)"
+                        )
+                with gr.Row():
+                    with gr.Column():
+                        top_p = gr.Slider(
+                            minimum=0.1, maximum=1.0, value=0.9, step=0.05,
+                            label="Top-p (Nucleus Sampling)"
+                        )
+            
+            output = gr.Textbox(
+                label="Model Output", 
+                lines=12,
+                show_copy_button=True
+            )
+        
+        with gr.Row():
+            gr.Markdown(
+                "⚡ Powered by Mistral's Devstral-Small-2505 - Optimized for code generation and technical tasks"
+            )
+    
+    submit_btn.click(
+        generate_text, 
+        inputs=[prompt, max_length, temperature, top_p], 
+        outputs=output
+    )
+    clear_btn.click(lambda: "", None, prompt)
+
+demo.launch()