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Load vectors in Language.from_config
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@ -1408,6 +1408,8 @@ class Language:
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nlp = cls(
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create_tokenizer=create_tokenizer, create_lemmatizer=create_lemmatizer,
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)
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if config["training"]["vectors"] is not None:
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util.load_vectors_into_model(nlp, config["training"]["vectors"])
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pipeline = config.get("components", {})
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for pipe_name in config["nlp"]["pipeline"]:
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if pipe_name not in pipeline:
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