-
Notifications
You must be signed in to change notification settings - Fork 46
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
- Loading branch information
Showing
1 changed file
with
16 additions
and
0 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,16 @@ | ||
This folder contains instructions to run the vLLM inference server. | ||
|
||
Some of the features include: | ||
|
||
1. Serialize HuggingFace models supported here to vLLM based format: https://github.com/vllm-project/vllm?tab=readme-ov-file#about | ||
2. Tensorizer support for fast model deserialization and loading from vLLM | ||
|
||
To run the example: | ||
|
||
1. Run `kubectl apply -f 00-optional-s3-secret.yaml` and replace access_key, secret_key and host_url | ||
2. Run `kubectl apply -f 01-optional-s3-serialize-job.yaml and replace --model EleutherAI/pythia-70m, --serialized-directory s3://my-bucket/ and optionally --suffix vllm | ||
3. Run `kubectl apply -f 02-inference-service.yaml and replace --model EleutherAI/pythia-70m and --model-loader-extra-config '{"tensorizer_uri": "s3://model-store/vllm/EleutherAI/pythia-70m/vllm/model.tensors"}' with your serialized model path | ||
|
||
You should have an inference service running a container with an OpenAI compatible server. | ||
|
||
You can use the client to interact with it. More information about the client can be found here: https://docs.vllm.ai/en/latest/getting_started/quickstart.html |