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.
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
Optimum-TPU provides a make tpu-tgi
command at the root level to help you create local docker image.
OPTIMUM_TPU_VERSION=0.1.0b1
docker run -p 8080:80 \
--net=host --privileged \
-v $(pwd)/data:/data \
-e HF_TOKEN=${HF_TOKEN} \
-e HF_BATCH_SIZE=1 \
-e HF_SEQUENCE_LENGTH=1024 \
huggingface/optimum-tpu:${OPTIMUM_TPU_VERSION}-tgi \
--model-id google/gemma-2b \
--max-concurrent-requests 4 \
--max-input-length 512 \
--max-total-tokens 1024 \
--max-batch-prefill-tokens 512 \
--max-batch-total-tokens 1024
You can query the model using either the /generate
or /generate_stream
routes:
curl 127.0.0.1:8080/generate \
-X POST \
-d '{"inputs":"What is Deep Learning?","parameters":{"max_new_tokens":20}}' \
-H 'Content-Type: application/json'
curl 127.0.0.1:8080/generate_stream \
-X POST \
-d '{"inputs":"What is Deep Learning?","parameters":{"max_new_tokens":20}}' \
-H 'Content-Type: application/json'