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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=True, | |
examples=[ | |
["What is the integral of x^2?"], | |
["How do I solve a quadratic equation?"] | |
], | |
theme="compact" | |
) | |
interface.launch() | |