SaveSpacy

API to save / load Spacy models.

Spacy models are composed of two files. The binary model and a configuration file.

While saving / loading models from GCP make sure to have credential saved into GOOGLE_APPLICATION_CREDENTIALS. If you don't you can download the access.json file from you GCP account and run this piece of code:

# Set enviroment variables
os.environ["TOKENIZERS_PARALLELISM"] = "false"
os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = acess_json_path

Local

load_model_local

Load a model from local files

config_file_path : str = Local path to load the config pickle bytes_model_path : str = Local path to load the model pickle

save_model_local

Save a model to local files

spacy_model : spacy.language = The Spacy model to save. config_path : str = Local path to save the config pickle model_path : str = Local path to save the model pickle

Google Cloud Storage

load_model_gcp

Load a model from GCS bucket

bucket_name : str = Name of Google Cloud Bucket to save the file. bucket_folder : str = The folder inside the bucket to save the file. If the folder doesn't exist it will be created. cfg_filename : str = Name of the configuration file (recommended cfg.pkl) bytes_filename : str = Name of the model file (recommended model.pkl)

save_model_gcp

Save a model to local GCS bucket.

This method first saved the model locally, then upload the files to GCS and finally remove the local files.

spacy_model : spacy.language = The spacy model to save. bucket_name: str = Name of Google Cloud Bucket to save the file. bucket_folder: str = The folder inside the bucket to save the file. If the folder doesn't exist it will be created. config_path: str = local path to save the cfg file model_path: str = local path to save the model file