https://github.com/whitew1994WW/aws-cdk-serverless-hugging-face
Forked from https://github.com/philschmid/sample-huggingface-sagemaker-c... which does the same for a real time endpoint.
Just posting her in case anyone else is always forgetting and needs a reference.
https://github.com/whitew1994WW/lambda-dual-style-gan
AWS Lambda is a lesser known powerhouse for machine learning. We demonstrate how you can bundle up a large generative model (8GB) into a Docker image for a serverless deployment, using parallel model loading to improve the inference time.Its not fast, but hey it is free.
- I wanted to see if I could, I hadn't done any NLP before :) - Some ingredient strings can be complex or contain multiple quantities/ingredients e.g. "3 1/2 cups icing sugar, plus 1/2 cup for dusting". "3 ripe avocados or guacamole" - I am interested to see what can be done with the ingredient embedding, perhaps for ingredient substitution - Hopefully the ML algorithm can learn to identify the unit and quantity based on context rather than a fixed list of ingredients
For far to long ingredient parsers been unavailable to the public. Either due to obsene complexity:https://github.com/nytimes/ingredient-phrase-taggerOr because of the dreaded paywall:https://github.com/mtlynch/zestful-clientWait no longer, I introduce PyIng. An easy to use python package for changing this "2 ounces of spicy melon" into this {name: melon, unit: ounces, qty:...