Learn About Our Meetup

4500+ Members

[P] Fitting (almost) any PyTorch module with just one line, including easy BERT fine-tuning

Hi everyone,

My name is Dima and I wanted to tell you about an open-source library we work on called TamnunML.

Our goal is to provide an easy to use library (with sklearn interface) for complex model training and fine-tuning. For example, with tamnun you can train any pytorch module like this:

“`python from torch import nn from tamnun.core import TorchEstimator

module = nn.Linear(128, 2) clf = TorchEstimator(module, task_type=’classification’).fit(train_X, train_y) “`

or, you can fine tune BERT on your task as easy as: “`python from tamnun.bert import BertClassifier, BertVectorizer from sklearn.pipeline import make_pipeline

clf = make_pipeline(BertVectorizer(), BertClassifier(num_of_classes=2)).fit(train_X, train_y) predicted = clf.predict(test_X) “`

At the moment tamnun supports training (almost) any pytorch module using just a “fit” method, easy BERT fine-tuning and model distillation.

You can read more about how to train (almost) any pytroch module with tamnun here

The library github page.

The introduction to TamnunML of the library we published in our blog.

submitted by /u/sudo_su_
[link] [comments]

Next Meetup




Plug yourself into AI and don't miss a beat


Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.