hierarchical-domain-adaptation
Code of NAACL 2022 "Efficient Hierarchical Domain Adaptation for Pretrained Language Models" paper. (by alexandra-chron)
pytorch-adapt
Domain adaptation made easy. Fully featured, modular, and customizable. (by KevinMusgrave)
| hierarchical-domain-adaptation | pytorch-adapt | |
|---|---|---|
| 1 | 3 | |
| 32 | 323 | |
| - | - | |
| 3.0 | 0.0 | |
| 8 months ago | over 1 year ago | |
| Python | Python | |
| - | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
hierarchical-domain-adaptation
Posts with mentions or reviews of hierarchical-domain-adaptation.
We have used some of these posts to build our list of alternatives
and similar projects.
-
AI2 Introduces Efficient Hierarchical Domain Adaptation for Pretrained Language Models
Github: https://github.com/alexandra-chron/hierarchical-domain-adaptation
pytorch-adapt
Posts with mentions or reviews of pytorch-adapt.
We have used some of these posts to build our list of alternatives
and similar projects.
- PyTorch-adapt re-purposes existing ML models to work in new domains
-
[P] A domain adaptation library that I wrote: PyTorch Adapt
For more details, you might be interested in the jupyter notebooks here: https://github.com/KevinMusgrave/pytorch-adapt/blob/main/examples/README.md
I wrote [a library](https://github.com/KevinMusgrave/pytorch-adapt) for domain adaptation, which is a type of machine learning that repurposes existing models to work in new domains. A toy example is adapting a model trained on MNIST for use on colored digits:
What are some alternatives?
When comparing hierarchical-domain-adaptation and pytorch-adapt you can also consider the following projects:
pykale - Knowledge-Aware machine LEarning (KALE): accessible machine learning from multiple sources for interdisciplinary research, part of the ð¥PyTorch ecosystem. â Star to support our work!
LLM-Adapters - Code for our EMNLP 2023 Paper: "LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models"
Transfer-Learning-Library - Transfer Learning Library for Domain Adaptation, Task Adaptation, and Domain Generalization
CEPC - A domain adaptation model
autogluon - AutoGluon: AutoML for Image, Text, Time Series, and Tabular Data [Moved to: https://github.com/autogluon/autogluon]