tgi¶
Helm chart for deploying Hugging Face Text Generation Inference service.
Installing the Chart¶
To install the chart, run the following:
cd GenAIInfra/helm-charts/common
export MODELDIR=/mnt/opea-models
export MODELNAME="bigscience/bloom-560m"
export HFTOKEN="insert-your-huggingface-token-here"
helm install tgi tgi --set global.modelUseHostPath=${MODELDIR} --set LLM_MODEL_ID=${MODELNAME} --set global.HUGGINGFACEHUB_API_TOKEN=${HFTOKEN}
# To deploy on Gaudi enabled kubernetes cluster
# helm install tgi tgi --set global.modelUseHostPath=${MODELDIR} --set LLM_MODEL_ID=${MODELNAME} --set global.HUGGINGFACEHUB_API_TOKEN=${HFTOKEN} --values gaudi-values.yaml
By default, the tgi service will downloading the “bigscience/bloom-560m” which is about 1.1GB.
If you already cached the model locally, you can pass it to container like this example:
MODELDIR=/mnt/opea-models
MODELNAME=”/data/models–bigscience–bloom-560m”
Verify¶
To verify the installation, run the command kubectl get pod
to make sure all pods are runinng.
Then run the command kubectl port-forward svc/tgi 2080:80
to expose the tgi service for access.
Open another terminal and run the following command to verify the service if working:
curl http://localhost:2080/generate \
-X POST \
-d '{"inputs":"What is Deep Learning?","parameters":{"max_new_tokens":17, "do_sample": true}}' \
-H 'Content-Type: application/json'
Values¶
Key |
Type |
Default |
Description |
---|---|---|---|
LLM_MODEL_ID |
string |
|
Models id from https://huggingface.co/, or predownloaded model directory |
global.HUGGINGFACEHUB_API_TOKEN |
string |
|
Hugging Face API token |
global.modelUseHostPath |
string |
|
Cached models directory, tgi will not download if the model is cached here. The host path “modelUseHostPath” will be mounted to container as /data directory. Set this to null/empty will force it to download model. |
image.repository |
string |
|
|
image.tag |
string |
|
|
horizontalPodAutoscaler.enabled |
bool |
false |
Enable HPA autoscaling for the service deployment based on metrics it provides. See HPA section before enabling! |