GEM-benchmark
By GEM-benchmark
OpenNMT
Open Source Neural Machine Translation in Torch (deprecated) (by OpenNMT)
| GEM-benchmark | OpenNMT | |
|---|---|---|
| 1 | 1 | |
| - | 2,338 | |
| - | - | |
| - | 10.0 | |
| - | about 4 years ago | |
| Lua | ||
| - | 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.
GEM-benchmark
Posts with mentions or reviews of GEM-benchmark.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-11-20.
-
WEBNLG challenge 2017 on Google Colab error
It looks like this uses the version of OpenNMT implemented in torch, which has been deprecated. You will be much better off using the pytorch implementation of OpenNMT or the transformers library. In fact, I would recommend taking a look at the GEM benchmark, since it also uses the WebNLG dataset. Here is a tutorial to get started, you can change the dataset here to WebNLG instead of CommonGen.
OpenNMT
Posts with mentions or reviews of OpenNMT.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-11-20.
-
WEBNLG challenge 2017 on Google Colab error
It looks like this uses the version of OpenNMT implemented in torch, which has been deprecated. You will be much better off using the pytorch implementation of OpenNMT or the transformers library. In fact, I would recommend taking a look at the GEM benchmark, since it also uses the WebNLG dataset. Here is a tutorial to get started, you can change the dataset here to WebNLG instead of CommonGen.
What are some alternatives?
When comparing GEM-benchmark and OpenNMT you can also consider the following projects:
OpenNMT-py - Open Source Neural Machine Translation and (Large) Language Models in PyTorch
WebNLG-Challenge-2017-test
transformers - 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.