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Loading large Huggingface models on Multiple GPUs

This document briefs on serving large HuggingFace (HF) models on multiple GPUs using deepspeed. We are using facebook/opt-30b in this example

Pre-requisites

  • Install CUDA. Verified to be working with CUDA 11.7.
  • Verified to be working with:
torch                   2.0.1+cu117
torch-model-archiver    0.8.2
torch-workflow-archiver 0.2.10
torchaudio              2.0.2+cu117
torchdata               0.6.1
torchserve              0.8.2
torchtext               0.15.2+cpu
torchvision             0.15.2+cu117
transformers            4.33.1
deepspeed               0.10.2

To run this example we need to have deepspeed installed. This has been added to the requirement.txt which can be bundled during model packaging.

pip install deepspeed

Step 1: Download model

python ../utils/Download_model.py --model_path model --model_name facebook/opt-30b --revision main

The script prints the path where the model is downloaded as below.

opt/model/models--facebook--opt-30b/snapshots/ceea0a90ac0f6fae7c2c34bcb40477438c152546

Step 2: Generate mar or tgz file

torch-model-archiver --model-name opt --version 1.0 --handler custom_handler.py --extra-files ds-config.json -r requirements.txt --config-file opt/model-config.yaml --archive-format tgz

Step 3: Add the tgz file to model store

mkdir model_store
mv opt.tar.gz model_store

Step 4: Start torchserve

torchserve --start --ncs --model-store model_store --models opt.tar.gz --disable-token-auth  --enable-model-api

Step 5: Run inference

curl  "http://localhost:8080/predictions/opt" -T sample_text.txt