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+ # Model description
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+
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+ - Morphosyntactic analyzer: Stanza
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+ - Tagset: UD
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+ - Embedding vectors: Fasttext (wiki)
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+ - Dataset: PDB (http://git.nlp.ipipan.waw.pl/alina/PDBUD/tree/master/PDB-UD/PDB-UD)
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+
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+ # How to use
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+
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+ ## Clone
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+
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+ ```
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+ git clone git@hf.co:ipipan/nlpre_stanza_ud_fasttext_pdb
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+ ```
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+
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+ ## Load model
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+
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+ ```
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+ import stanza
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+ lang = 'pl'
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+ model_name = 'nlpre_stanza_ud_fasttext_pdb'
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+ prefix = 'pdb1809'
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+ config = \
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+ {
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+ # Comma-separated list of processors to use
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+ 'processors': 'tokenize,mwt,pos,lemma',
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+ # Language code for the language to build the Pipeline in
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+ 'lang': lang,
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+ # Processor-specific arguments are set with keys "{processor_name}_{argument_name}"
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+ # You only need model paths if you have a specific model outside of stanza_resources
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+ 'tokenize_model_path': os.path.join(model_name, f'{lang}_{prefix}_tokenizer.pt'),
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+ 'mwt_model_path': os.path.join(model_name, f'{lang}_{prefix}_mwt_expander.pt'),
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+ 'pos_model_path': os.path.join(model_name, f'{lang}_{prefix}_tagger.pt'),
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+ 'pos_pretrain_path': os.path.join(model_name, f'{lang}_{prefix}.pretrain.pt'),
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+ 'lemma_model_path': os.path.join(model_name, f'{lang}_{prefix}_lemmatizer.pt'),
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+ # Use pretokenized text as input and disable tokenization
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+ 'tokenize_pretokenized': True
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+ }
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+ model = stanza.Pipeline(**config)