Spaces:
Runtime error
Runtime error
| import gradio as gr | |
| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| import torch | |
| model_name = "mistralai/Devstral-Small-2505" | |
| tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-v0.1", use_fast=False) | |
| model = AutoModelForCausalLM.from_pretrained( | |
| model_name, | |
| torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32 | |
| ) | |
| device = "cuda" if torch.cuda.is_available() else "cpu" | |
| model = model.to(device) | |
| def code_completion(prompt, max_new_tokens=128, temperature=0.2): | |
| if not prompt.strip(): | |
| return "Please enter some code to complete." | |
| inputs = tokenizer(prompt, return_tensors="pt").to(device) | |
| with torch.no_grad(): | |
| outputs = model.generate( | |
| **inputs, | |
| max_new_tokens=max_new_tokens, | |
| temperature=temperature, | |
| do_sample=True, | |
| pad_token_id=tokenizer.eos_token_id | |
| ) | |
| generated = tokenizer.decode(outputs[0], skip_special_tokens=True) | |
| return generated[len(prompt):] | |
| custom_css = """ | |
| body {background: #f7f8fa;} | |
| .gradio-container {background: #f7f8fa;} | |
| h1, h2, h3, h4, h5, h6 {font-family: 'Inter', sans-serif;} | |
| #main-title { | |
| text-align: center; | |
| font-weight: 800; | |
| font-size: 2.3em; | |
| margin-bottom: 0.2em; | |
| letter-spacing: -1px; | |
| color: #222; | |
| } | |
| #subtitle { | |
| text-align: center; | |
| color: #6c6f7a; | |
| font-size: 1.1em; | |
| margin-bottom: 2em; | |
| } | |
| .gr-box {border-radius: 16px;} | |
| """ | |
| with gr.Blocks(css=custom_css, theme=gr.themes.Soft()) as demo: | |
| gr.Markdown( | |
| """ | |
| <h1 id="main-title">Devstral Code Autocomplete</h1> | |
| <div id="subtitle">Minimal, beautiful code completion powered by <b>Devstral</b></div> | |
| """) | |
| with gr.Row(): | |
| with gr.Column(scale=1): | |
| prompt = gr.Textbox( | |
| label="Your code prompt", | |
| lines=10, | |
| placeholder="def quicksort(arr):\n \"\"\"Sort the array using quicksort algorithm.\"\"\"\n if len(arr) <= 1:\n return arr\n pivot = arr[len(arr) // 2]\n ", | |
| show_copy_button=True, | |
| autofocus=True | |
| ) | |
| with gr.Row(): | |
| max_tokens = gr.Slider(16, 256, value=128, step=8, label="Max new tokens") | |
| temperature = gr.Slider(0.1, 1.0, value=0.2, step=0.05, label="Temperature") | |
| btn = gr.Button("Generate Completion", elem_id="generate-btn") | |
| with gr.Column(scale=1): | |
| output = gr.Code( | |
| label="Generated code", | |
| language="python", | |
| lines=12, | |
| interactive=False | |
| ) | |
| btn.click(code_completion, inputs=[prompt, max_tokens, temperature], outputs=output) | |
| demo.launch() |