Google TPUs documentation

Deploying a Text-Generation Inference server on a Google Cloud TPU instance

Hugging Face's logo
Join the Hugging Face community

and get access to the augmented documentation experience

to get started

Deploying a Text-Generation Inference server on a Google Cloud TPU instance

Context

Text-Generation-Inference (TGI) is a highly optimized serving engine enabling serving Large Language Models (LLMs) in a way that better leverages the underlying hardware, Cloud TPU in this case.

Deploy TGI on Cloud TPU instance

We assume the reader already has a Cloud TPU instance up and running. If this is not the case, please see our guide to deploy one here

Docker Container Build

Optimum-TPU provides a make tpu-tgi command at the root level to help you create local docker image.

Docker Container Run

HF_TOKEN=<your_hf_token_here>
MODEL_ID=google/gemma-2b

sudo docker run --net=host \
                --privileged \
                -v $(pwd)/data:/data \
                -e HF_TOKEN=${HF_TOKEN} \
                huggingface/optimum-tpu:latest \
                --model-id ${MODEL_ID} \
                --max-concurrent-requests 4 \
                --max-input-length 32 \
                --max-total-tokens 64 \
                --max-batch-size 1

Executing requests against the service

You can query the model using either the /generate or /generate_stream routes:

curl localhost/generate \
    -X POST \
    -d '{"inputs":"What is Deep Learning?","parameters":{"max_new_tokens":20}}' \
    -H 'Content-Type: application/json'
curl localhost/generate_stream \
    -X POST \
    -d '{"inputs":"What is Deep Learning?","parameters":{"max_new_tokens":20}}' \
    -H 'Content-Type: application/json'