| # numbers_gcd | |
| --- | |
| language: en | |
| datasets: | |
| - numbers_gcd | |
| --- | |
| This is a [t5-small](https://ai.googleblog.com/2020/02/exploring-transfer-learning-with-t5.html) fine-tuned version on the [math_dataset/numbers_gcd](https://www.tensorflow.org/datasets/catalog/math_dataset#mathdatasetnumbers_gcd) for solving **greatest common divisor** mission. | |
| To load the model: | |
| (necessary packages: !pip install transformers sentencepiece) | |
| ```python | |
| from transformers import AutoTokenizer, AutoModelWithLMHead | |
| tokenizer = AutoTokenizer.from_pretrained("dbernsohn/t5_numbers_gcd") | |
| model = AutoModelWithLMHead.from_pretrained("dbernsohn/t5_numbers_gcd") | |
| ``` | |
| You can then use this model to solve algebra 1d equations into numbers. | |
| ```python | |
| query = "What is the highest common factor of 4210884 and 72?" | |
| 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> 36</s> | |
| ``` | |
| Another examples: | |
| + Calculate the greatest common factor of 3470 and 97090. | |
| + Answer: 10 Pred: 10 | |
| ---- | |
| + Calculate the highest common factor of 3480 and 775431. | |
| + Answer: 87 Pred: 87 | |
| ---- | |
| + What is the highest common divisor of 26 and 88049? | |
| + Answer: 13 Pred: 13 | |
| ---- | |
| + Calculate the highest common factor of 1416 and 24203688. | |
| + Answer: 1416 Pred: 1416 | |
| ---- | |
| + Calculate the highest common divisor of 124 and 69445828. | |
| + Answer: 124 Pred: 124 | |
| ---- | |
| + What is the greatest common factor of 657906 and 470? | |
| + Answer: 94 Pred: 94 | |
| ---- | |
| + What is the highest common factor of 4210884 and 72? | |
| + Answer: 36 Pred: 36 | |
| 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/) | |