From 91cd4f364cea0ae1de859af0b7af7952cd2ab8a5 Mon Sep 17 00:00:00 2001 From: GokuMohandas Date: Wed, 20 Mar 2024 21:41:54 -0700 Subject: [PATCH] small fixes --- docs/courses/mlops/jobs-and-services.md | 12 ++++++++++++ docs/templates/instructor.md | 2 +- 2 files changed, 13 insertions(+), 1 deletion(-) diff --git a/docs/courses/mlops/jobs-and-services.md b/docs/courses/mlops/jobs-and-services.md index 9ca565d1..257c6c0e 100644 --- a/docs/courses/mlops/jobs-and-services.md +++ b/docs/courses/mlops/jobs-and-services.md @@ -170,6 +170,18 @@ subprocess.check_output(["aws", "s3", "cp", f"s3://madewithml/{github_username}/ # Entrypoint run_id = [line.strip() for line in open("run_id.txt")][0] entrypoint = ModelDeployment.bind(run_id=run_id, threshold=0.9) + +# Inference +data = {"query": "What is the default batch size for map_batches?"} +response = requests.post("http://127.0.0.1:8000/query", json=data) +print(response.json()) + + +# Inference +data = {"query": "What is the default batch size for map_batches?"} +response = requests.post("http://127.0.0.1:8000/query", json=data) +print(response.json()) + ``` In this script, we first pull our previously saved artifacts from our S3 bucket to our local storage and then define the entrypoint for our model. diff --git a/docs/templates/instructor.md b/docs/templates/instructor.md index f9cc1fc5..dde5fd77 100644 --- a/docs/templates/instructor.md +++ b/docs/templates/instructor.md @@ -18,7 +18,7 @@

- While this was an amazing experience, it was also a humbling one because there were obstacles around scale, integrations and productionization that I that I didn’t have great solutions for. So, I decided to join a team that has been addressing these precise obstacles with some of the best ML teams in the world and has an even bigger vision I could stand behind. So I'm excited to announce that Made With ML is now part of Anyscale to accelerate the path towards production ML. + While this was an amazing experience, it was also a humbling one because there were obstacles around scale, integrations and productionization that I didn’t have great solutions for. So, I decided to join a team that has been addressing these precise obstacles with some of the best ML teams in the world and has an even bigger vision I could stand behind. So I'm excited to announce that Made With ML is now part of Anyscale to accelerate the path towards production ML.