import torch from transformers import AutoTokenizer, AutoModelForCausalLM import gradio as gr # Load tokenizer and model tokenizer = AutoTokenizer.from_pretrained("deepseek-ai/deepseek-math-7b-instruct") model = AutoModelForCausalLM.from_pretrained("deepseek-ai/deepseek-math-7b-instruct", torch_dtype=torch.bfloat16, device_map="cpu") from transformers import GenerationConfig model.generation_config = GenerationConfig.from_pretrained("deepseek-ai/deepseek-math-7b-instruct") model.generation_config.pad_token_id = model.generation_config.eos_token_id def solve_math_problem(questions): if isinstance(questions, str): # If input is a single string questions = [questions] results = [] for question in questions: messages = [{"role": "user", "content": question}] input_tensor = tokenizer.apply_chat_template(messages, add_generation_prompt=True, return_tensors="pt") outputs = model.generate(input_tensor.to(model.device), max_new_tokens=100) result = tokenizer.decode(outputs[0][input_tensor.shape[1]:], skip_special_tokens=True) results.append(result) return results interface = gr.Interface( fn=solve_math_problem, inputs="text", outputs="text", title="Math Wizard", description=""" Welcome to the Math Wizard! Ask any math question, and let the wizard guide you through the solution step-by-step. """, allow_flagging=True, examples=[ ["What is the integral of x^2?"], ["How do I solve a quadratic equation?"] ], theme="compact" ) interface.launch()