This is a text generation method which returns a generator, streaming out each token in real-time during inference, based on Huggingface/Transformers.

• original
• stream

pip install transformers-stream-generator

1. just add two lines of code before your original code

from transformers_stream_generator import init_stream_support
init_stream_support()

2. add do_stream=True in model.generate function and keep do_sample=True, then you can get a generator

generator = model.generate(input_ids, do_stream=True, do_sample=True)
for token in generator:
    word = tokenizer.decode(token)
    print(word)

• run python script example by gpt2
• run web example by gpt2 and test in client example