This is a text generation method which returns a generator, streaming out each token in real-time during inference, based on Huggingface/Transformers.
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Author: LowinLi
Requires Python: >=3.5
Classifiers
Intended Audience
- Developers
Topic
- Scientific/Engineering :: Artificial Intelligence
License
- OSI Approved :: Apache Software License
Programming Language
- Python :: 3
- Python :: 3.5
- Python :: 3.6
- Python :: 3.7
- Python :: 3.8
- Python :: 3.9
- Python :: 3.10
transformers-stream-generator
Description
This is a text generation method which returns a generator, streaming out each token in real-time during inference, based on Huggingface/Transformers.
Web Demo
- original
- stream
Installation
pip install transformers-stream-generator
Usage
- just add two lines of code before your original code
from transformers_stream_generator import init_stream_support
init_stream_support()
- add
do_stream=True
inmodel.generate
function and keepdo_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)
Example
Files in release
No dependencies