Models to perform neural summarization (extractive and abstractive) using machine learning transformers and a tool to convert abstractive summarization datasets to the extractive task.
When I tried executing a part in extractive, I get the following error
ValueError: [E966] `nlp.add_pipe` now takes the string name of the registered component factory, not a callable component. Expected string, but got <spacy.pipeline.sentencizer.Sentencizer object at 0x7f9fde2b6080> (name: 'None').
- If you created your component with `nlp.create_pipe('name')`: remove nlp.create_pipe and call `nlp.add_pipe('name')` instead.
- If you passed in a component like `TextCategorizer()`: call `nlp.add_pipe` with the string name instead, e.g. `nlp.add_pipe('textcat')`.
- If you're using a custom component: Add the decorator `@Language.component` (for function components) or `@Language.factory` (for class
components / factories) to your custom component and assign it a name, e.g. `@Language.component('your_name')`. You can then run `nlp.ad
d_pipe('your_name')` to add it to the pipeline.
which can be resolved by this PR.
Essentially, the name needs to be passed into nlp.add_pipe, instead of the Sentencizer
HHousen
commented
1 year ago
When I tried executing a part in
extractive, I get the following errorwhich can be resolved by this PR.
Essentially, the name needs to be passed into
nlp.add_pipe, instead of the Sentencizer