| | import gradio as gr |
| | import torch |
| | from transformers import AutoModelForCausalLM, AutoTokenizer |
| | import spaces |
| |
|
| | |
| | model_name = "Qwen/Qwen2.5-Coder-1.5B-Instruct" |
| |
|
| | def load_model(): |
| | model = AutoModelForCausalLM.from_pretrained( |
| | model_name, |
| | torch_dtype=torch.float16, |
| | device_map="auto", |
| | low_cpu_mem_usage=True |
| | ) |
| | tokenizer = AutoTokenizer.from_pretrained(model_name) |
| | return model, tokenizer |
| |
|
| | model, tokenizer = load_model() |
| |
|
| | @spaces.GPU(duration=60) |
| | def fix_code(input_code): |
| | messages = [ |
| | {"role": "system", "content": "You are a helpful coding assistant. Please analyze the following code, identify any errors, and provide the corrected version."}, |
| | {"role": "user", "content": f"Please fix this code:\n\n{input_code}"} |
| | ] |
| | |
| | text = tokenizer.apply_chat_template( |
| | messages, |
| | tokenize=False, |
| | add_generation_prompt=True |
| | ) |
| | |
| | model_inputs = tokenizer([text], return_tensors="pt").to(model.device) |
| | generated_ids = model.generate( |
| | **model_inputs, |
| | max_new_tokens=1024, |
| | temperature=0.7, |
| | top_p=0.95, |
| | ) |
| | |
| | generated_ids = [ |
| | output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids) |
| | ] |
| | response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0] |
| | |
| | return response |
| |
|
| | iface = gr.Interface( |
| | fn=fix_code, |
| | inputs=gr.Code( |
| | label="Input Code", |
| | language="python", |
| | lines=10 |
| | ), |
| | outputs=gr.Code( |
| | label="Corrected Code", |
| | language="python", |
| | lines=10 |
| | ), |
| | title="Code Correction Tool", |
| | description="Enter your code with errors, and the AI will attempt to fix it.", |
| | examples=[ |
| | ["def fibonacci(n):\n if n = 0:\n return 0\n elif n == 1\n return 1\n else:\n return fibonacci(n-1) + fibonacci(n-2)"], |
| | ["for i in range(10)\n print(i"] |
| | ] |
| | ) |
| |
|
| | if __name__ == "__main__": |
| | iface.launch() |