en_vectors_web_lg renamed to en_core_web_lg in https://prodi.gy/docs

Small change; had to rename this to get the Prodigy 101 tutorial to work for NER at https://prodi.gy/docs#first-steps3

In this example, we’re training with 372 total annotations and are using the large [`en_vectors_web_lg` model](https://spacy.io/models/en#en_vectors_web_lg) as the base model. The vectors will be used as features during training, which can give you a nice boost in accuracy. If you don’t have the vector package installed yet, you can download it via `spacy download en_vectors_web_lg` . If you don’t provide an `--eval-id` argument with the name of an evaluation set to evaluate against, Prodigy will hold back a percentage of examples for evaluation, so you can see how your model does on unseen data.

Thanks for the note!

For the current stable version of prodigy (still using spaCy v2), the link for en_vectors_web_lg should point to: https://v2.spacy.io/models/en-starters

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