spaCy
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explosion
💫 Industrial-strength Natural Language Processing (NLP) in Python
## How to reproduce the behaviour Add a PyTorchWrapper component to a language pipeline and then do this: ``` nlp.to_disk("something") nlp2 = spacy.load("something") ``` Motivating case is covered in https://github.com/explosion/spaCy/discussions/8291....
Currently there's a default background color for entities in [displacy](https://github.com/explosion/spaCy/blob/master/spacy/displacy/render.py#L13) It would be nice to be able to provide with a different default color. It seems like a pretty easy...
I am trying to continue training an NER model. I have done this in spaCy 3.0.6 in the past numerous times, but after coming back to do it again, I...
Getting OOM while inferencing documents using the spacy Transformer model. The GPU memory is not getting free up when doc object get created.
## How to reproduce the behaviour When prioritizing vectors to keep, `Vocab.prune_vectors` doesn't handle existing duplicates from `key2row` well. By sorting/prioritizing by values from `key2row`, which may contain duplicate values,...
## How to reproduce the behaviour I was planning to have a look at the [example projects](https://github.com/explosion/projects/blob/v3/pipelines/tagger_parser_ud/project.yml) and quickly found that these are very Linux oriented. The commands are all...
## How to reproduce the behaviour I cannot reproduce the same results when training a NER model using GPU in Google Colab. When running the same code with CPU it...
## Feature description The [Matcher](https://spacy.io/api/matcher) supports `!`, `?`, `+`, and `*` [operators and quantifiers](https://spacy.io/usage/rule-based-matching#quantifiers). I have text where it would be useful to have something like the regex lookaround patterns,...
Hi. Here is an issue I'm getting using some French pipelines (fr_core_news_lg or fr_dep_news_trf). As you can see it works in some cases but fetches the wrong lemma in some...
## How to reproduce the behaviour ### With SpaCy 3.0.0: ``` nlp = spacy.load("en_core_web_trf") # same result with en_core_web_lg doc = nlp("Can't go to school") print([(token.text, token.lemma_) for token in...
