The Python dependencies for each example are captured in requirements.txt in the corresponding ML task directory (e.g. ./text-generation).
Python dependencies can be installed using:
pip install -r requirements.txt
For the ./automatic-speech-recognition/test-wav2vec.py speech model example, you may also need to install the libsndfile1-dev generic library:
sudo apt-get install libsndfile1-dev
The DeepSpeed huggingface inference examples are organized into their corresponding ML task directories (e.g. ./text-generation). Each ML task directory contains a README.md and a requirements.txt.
Most examples can be run as follows:
deepspeed --num_gpus [number of GPUs] test-[model].py
Information about DeepSpeed can be found at the deepspeed.ai website.
Additional information on DeepSpeed inference can be found here:
DeepSpeed inference benchmarking can be found in the DeepSpeed repository: