nlp | Comparison of three NLP services : AlchemyAPI | Natural Language Processing library

Most labels have definitions you can access using spacy.explain(label).

For NORP: "Nationalities or religious or political groups"

For more details you would need to look into the annotation guidelines for the resources listed in the model documentation under https://spacy.io/models/.

You should download and install the language package.

You end up with the error with precision because some of your penalization is too strong for this model, if you check the results, you get 0 for f1 score when C = 0.001 and C = 0.01

You need to append i to nb_and after each sentence is processed:

If you can find distilbert folder in your pc, you can see vocabulary is basically txt file that contains only one column. You can do whatever you want to do.

The ZeroShotClassificationPipeline is currently not supported by shap, but you can use a workaround. The workaround is required because:

1. The shap Explainer forwards only one parameter to the model (a pipeline in this case), but the ZeroShotClassificationPipeline requires two parameters, namely text, and labels.
2. The shap Explainer will access the config of your model and use its label2id and id2label properties. They do not match the labels returned from the ZeroShotClassificationPipeline and will result in an error.

Below is a suggestion for one possible workaround. I recommend opening an issue at shap and requesting official support for huggingface's ZeroShotClassificationPipeline.

Two minor errors that's preventing you from looping through. For the second example, in the for loop you're only looping through index 0 and index (len(human_directory) - 1)). Instead, you should do for i in range(len(human_directory)): That should allow you to loop through both.

For the first, I think you might get some kind of too many values to unpack error. To loop through two iterables concurrently, use zip(), so it should look like

for human_file, api_file in zip(os.listdir(human_directory), os.listdir(api_directory)):

The strings in question are split into two tokens:

Are you sure you did install spacy-transformers? After installing spacy?

I am using pip: pip install spacy-transformers and I have no problems loading the en_core_web_trf.