[marvinalone]

It depends on what you use AllenNLP for. AllenNLP has a ton of functionality for vectorizing text. Most of the tokenizer/indexer/embedder stuff is about that. But these days we all use transformers for that, so there isn't much of a need to experiment with ways to vectorize.

If you like the trainer, or the configuration language, or some of the other components you should check out Tango (https://github.com/allenai/tango). One of Tango's origins is the question "What if AllenNLP supported workflow steps other than read -> train -> evaluate?". We noticed that a lot of work in NLP no longer fit that simple pattern, so we needed a new tool that can support more complex experiments.

If you like the metrics, try torchmetrics. Torchmetrics has almost exactly the same API as AllenNLP metrics.

If you like any of the nn components, please get in touch with the Tango team (on GitHub). We recently had some discussion around rescuing a few of those, since there seems to be some excitement.