Import transformer model into spacy v3

transformer.py

from thinc.api import Config
import spacy

DEFAULT_CONFIG_STR = """
[transformer]
max_batch_items = 4096

[transformer.set_extra_annotations]
@annotation_setters = "spacy-transformers.null_annotation_setter.v1"

[transformer.model]
@architectures = "spacy-transformers.TransformerModel.v3"
name = "shc-cn-v2"
tokenizer_config = {"use_fast": true}
transformer_config = {}
mixed_precision = false
grad_scaler_config = {}

[transformer.model.get_spans]
@span_getters = "spacy-transformers.strided_spans.v1"
window = 128
stride = 96
"""
DEFAULT_CONFIG = Config().from_str(DEFAULT_CONFIG_STR)

nlp = spacy.blank("pt")
trf = nlp.add_pipe("transformer", config=DEFAULT_CONFIG["transformer"])
trf.model.initialize()

doc = nlp('text here')