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Deploy transformers serverless on AWS Lambda

License: Apache License 2.0

Dockerfile 5.92% Python 94.08%

serverless-transformers-on-aws-lambda's Introduction

End2End Serverless Transformers On AWS Lambda for NLP ๐Ÿš€

You need no servers

Deploy transformers with ease ๐Ÿ’†โ€โ™‚๏ธ

Go through this slide deck for full info

Current available pipelines

  1. classification
  2. translation (coming soon)
  3. token classification
  4. text generation (need contribution)
  5. zero shot classification

What you get with this?

  • ability to run transformers without servers
  • complete CI/CD
  • concurrency upto 1000 (default AWS limit)

How to use this?

  • clone the repo
  • keep the pipeline folder you want to use
  • modify the source and tests
  • keep the corresponding github action in .github/workflows
  • modify directory, registry and lambda function name in workflow
  • create repository in AWS ECR
  • set up secrets in repo (needed for access to AWS; this creds should have access to ECR and Lambda)
    • AWS_ACCESS_KEY_ID
    • AWS_SECRET_ACCESS_KEY
  • push the code
  • create PR
    • this will build the container
    • run all the tests
    • push container to ECR registry
    • update lambda with the new container (this will not happen when you push the first time)
  • create lambda function if it does not exist
    • give appropriate IAM role
    • set timeout and RAM
  • create API in API gateway and link to lambda

Done! Now you can call the lambda using the API

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