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dbernsohn/t5_numbers_gcd
t5_numbers_gcd is a machine learning model from dbernsohn. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers.
--- language: en datasets: - numbersgcd ---
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From the Hugging Face model README
language: en datasets:
This is a t5-small fine-tuned version on the math_dataset/numbers_gcd for solving greatest common divisor mission.
To load the model: (necessary packages: !pip install transformers sentencepiece)
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.
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:
The whole training process and hyperparameters are in my GitHub repo
Created by Dor Bernsohn