DeepPavlov | open source library for deep learning end | Natural Language Processing library

$ pip3 install -r requirements.txt

from deeppavlov import build_model

# Download and load model (set download=False to skip download phase)
ner = build_model("./ner_bert_slav.json", download=True)

# Get predictions
ner(["To Bert z ulicy Sezamkowej  

  deeppavlov-lhcchatbot-german:
    build: ./Dockerfiles/deep
    environment:
      - LHC_API=train_tfidf_logreg_en_faq.json
    container_name: deeppavlov-lhcchatbot-german
    image: remdex/deeppavlov-lhcchatbot:latest
    ports:
      - "5005:500  

# Export trainings Adjust paths!
cd `lhc_web/` && /usr/bin/php cron.php -s site_admin -e lhcchatbot -c cron/deeppavlov_train

# Copy trainings. Adjust paths!
cd ../ && cp extension/lhcchatbot/train/* /deeppavlov/Dockerfiles/deep/trai  

model_config = read_json(configs.faq.tfidf_logreg_en_faq)
model_config["dataset_reader"]["data_path"] = ''
model_config["dataset_reader"]["data_url"] = "your-dataset-link"

faq = train_model(model_config)
answer = faq(["help"])
answer

answers_list, answers_starts_list, logits_list

from deeppavlov import build_model, configs
model = build_model(configs.squad.squad_bert)
model(['DeepPavlov is library for NLP and dialog systems.'], ['What is DeepPa

from deeppavlov import build_model, configs

ner_model = build_model(configs.ner.ner_ontonotes, download=True)
ner_model(['Computer Sciences Corp . , El Segundo , Calif . , said it is close to making final an agreement to buy Cleveland Con

import json
from deeppavlov import configs, build_model, train_model

with configs.ner.ner_ontonotes_bert_mult.open(encoding='utf8') as f:
    ner_config = json.load(f)

ner_config['dataset_reader']['data_path'] = '~/my_data_dir/'  # direc

"goals": {"food": "dontcare", "pricerange": "cheap", "area": "south"},
"db_result": null,
"dialog-acts": [{"slots": [], "act": "thankyou"}, {"slots": [], "act": "bye"}]}

import os
from deeppavlov import build_model

!pip install deeppavlov

from deeppavlov.deep import find_config
from deeppavlov.core.commands.infer import build_model
config_path = find_config('elmo_ru-wiki')
model = build_model(config_path, load_trained = True, download = True)
a = mo