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outline Zero base -1] PaddlePaddle learn Bert_ One blog - CSDN bloghttps://blog.csdn.net/qq_42276781/article/details/121488335 Cell 3 # Call tokenizer for bert model tokenizer = ppnlp.transformers.BertTokenizer.from_pretrained('bert-base-chinese') inputs_1 = tokenizer('What a nice day today') print(inputs_1) inputs_2 = tokenizer('Will it rai ...

The last article was mainly about installation. In fact, there are two problems later. After installing TensorFlow, anaconda prompt reports an error and anaconda can't open Problem solving 1.anaconda prompt reports an error Maybe the following problem occurs. As long as you open prompt, it will appear and you can't input instructions. The on ...

1, Service deployment PyZMQ is implemented in Python using zeroMQ, which provides a lightweight and fast messaging implementation. A simple example of using C/S messaging is as follows: import zmq import zmq.decorators as zmqd @zmqd.socket(zmq.PUSH) def send(sock): sock.bind('tcp://*:5555') sock.send(b'hello') # in another process ...

1. Pre-training methods for HF models trainer training using tokenizer and MLM packages from HF home page 1. Loading datasets: Selecting multilingual and multilingual datasets OSCAR corpus # in this notebook we'll only get one of the files (the Oscar one) for the sake of simplicity and performance !wget -c https://cdn-datasets.huggingfa ...

NLP star sky intelligent dialogue robot series for natural language processing: in depth understanding of Transformer Workshop on Machine Translation (WMT) Machine transductions and translations The evaluation of machine translation shows the progress of natural language processing technology. To determine that one solution is better than ...