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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=False,
examples=[
["What is the integral of x^2?"],
["How do I solve a quadratic equation?"],
["Tell me about Ramanujan"]
]
)
if __name__ == "__main__":
interface.launch()
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