Update README.md
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README.md
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- split: test
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path: data/test-*
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---
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- split: test
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path: data/test-*
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---
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# Simple Math
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Just like my teacher gave me homework, i thought maybe we can also add some of these basics on the trainings of our models.
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It was created with this code, if you add more complex operations and so.. please share the code :D thank you
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```
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import random
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# Define the number of samples you want to generate
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num_samples = 500000
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# Define the range for the random numbers
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min_value = -99.99
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max_value = 99.99
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# Define the arithmetic operations
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operations = ['+', '-', '*', '/']
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# Generate data
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data = []
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for _ in range(num_samples):
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num1 = float("%.3f" % random.uniform(min_value, max_value))
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num2 = float("%.3f" % random.uniform(min_value, max_value))
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while num2 == 0.0:
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num2 = float("%.3f" % random.uniform(min_value, max_value))
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while num1 == 0.0:
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num1 = float("%.3f" % random.uniform(min_value, max_value))
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operation = random.choice(operations)
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if operation == '/':
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result = num1 / num2
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elif operation == '-':
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result = num1 - num2
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elif operation == '*':
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result = num1 * num2
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elif operation == '+':
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result = num1 + num2
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output = "%.4f" % result
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instruction = f"{num1} {operation} {num2}"
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data.append({'instruction': instruction, 'output': output})
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# Create the dataset
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import json
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out_file = 'arithmetic-float4a.json'
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with open(out_file, 'w') as f:
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json.dump(data, f)
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```
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If you use Simple Math o train your model, please cite on the modelcard or the paper.
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Thank you
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