| # algebra_linear_1d_composed | |
| --- | |
| language: en | |
| datasets: | |
| - algebra_linear_1d_composed | |
| --- | |
| This is a [t5-small](https://ai.googleblog.com/2020/02/exploring-transfer-learning-with-t5.html) fine-tuned version on the [math_dataset/algebra_linear_1d_composed](https://www.tensorflow.org/datasets/catalog/math_dataset#mathdatasetalgebra_linear_1d_composed) for solving **algebra linear 1d composed equations** mission. | |
| To load the model: | |
| (necessary packages: !pip install transformers sentencepiece) | |
| ```python | |
| from transformers import AutoTokenizer, AutoModelWithLMHead | |
| tokenizer = AutoTokenizer.from_pretrained("dbernsohn/algebra_linear_1d_composed") | |
| model = AutoModelWithLMHead.from_pretrained("dbernsohn/algebra_linear_1d_composed") | |
| ``` | |
| You can then use this model to solve algebra 1d equations into numbers. | |
| ```python | |
| query = "Suppose -d = 5 - 16. Let b = -579 + 584. Solve -b*c + 36 = d for c." | |
| input_text = f"{query} </s>" | |
| features = tokenizer([input_text], return_tensors='pt') | |
| model.to('cuda') | |
| output = model.generate(input_ids=features['input_ids'].cuda(), | |
| attention_mask=features['attention_mask'].cuda()) | |
| tokenizer.decode(output[0]) | |
| # <pad> 5</s> | |
| ``` | |
| Another examples: | |
| + Suppose -d = 5 - 16. Let b = -579 + 584. Solve -b*c + 36 = d for c. | |
| + Answer: 5 Pred: 5 | |
| ---- | |
| + Suppose 3*v - l + 9 = 4*v, 0 = -5*v + 5*l - 5. Let f(s) = 3*s**2 + 1. Let g be f(-1). Suppose 63 = g*x - x. Solve -5*i + v + x = 0 for i. | |
| + Answer: 5 Pred: 5 | |
| ---- | |
| + Let w be 2 - (0 - 0)/(-2). Let f = -110 - -110. Suppose f*m - 4*m + 3*m = 0. Solve m*v = -w*v for v. | |
| + Answer: 0 Pred: 0 | |
| ---- | |
| + Let a(h) = -34*h**3 - 15 + 3*h + 36*h**3 + 8*h**2 + 5*h**2. Let r be a(-6). Solve 2*z = r*z for z. | |
| + Answer: 0 Pred: 0 | |
| ---- | |
| + Suppose -3*p + 24 = -3*c, 0*c + 6 = -2*c. Suppose -67 = 4*i + 289. Let t = i + 94. Solve t = 2*y - p for y. | |
| + Answer: 5 Pred: 5 | |
| ---- | |
| + Let b = -36 + 53. Suppose -7*u - b = -73. Solve j + 3*j = -u for j. | |
| + Answer: -2 Pred: -2 | |
| ---- | |
| + Let h be 8*((-2)/2 + 14)*1. Let y = -101 + h. Solve y*p = -p for p. | |
| + Answer: 0 Pred: 0 | |
| ---- | |
| + Let b = 178 - 79. Let s be 9/(-1 - 2 - b/(-22)). Solve s = -k - k for k. | |
| + Answer: -3 Pred: -3 | |
| ---- | |
| + Suppose 31 = -4*z + 11, -3*k - 5*z - 22 = 0. Solve 23 = -11*p + k for p. | |
| + Answer: -2 Pred: -2 | |
| The whole training process and hyperparameters are in my [GitHub repo](https://github.com/DorBernsohn/CodeLM/tree/main/MathLM) | |
| > Created by [Dor Bernsohn](https://www.linkedin.com/in/dor-bernsohn-70b2b1146/) | |