Downloads · 30 days
12
2% of all-time downloads
dbernsohn/t5_measurement_time
t5_measurement_time 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: - measurementtime ---
Downloads · 30 days
12
2% of all-time downloads
All-time downloads
621
Public
Repo size
727 MB
Likes
1
Public
Click a slice to open those files.
.bin242 MB · 100%
From the Hugging Face model README
language: en datasets:
This is a t5-small fine-tuned version on the math_dataset/measurement_time for solving measurement time equations mission.
To load the model: (necessary packages: !pip install transformers sentencepiece)
from transformers import AutoTokenizer, AutoModelWithLMHead
tokenizer = AutoTokenizer.from_pretrained("dbernsohn/t5_measurement_time")
model = AutoModelWithLMHead.from_pretrained("dbernsohn/t5_measurement_time")
You can then use this model to solve algebra 1d equations into numbers.
query = "How many minutes are there between 2:09 PM and 2:27 PM?"
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> 18</s>
Another examples:
The whole training process and hyperparameters are in my GitHub repo
Created by Dor Bernsohn