Hi! I’m new to hugging face, so excuse this if it’s a dumb question!
I’m trying to expose the T5 small pre_trained model as a REST endpoint. I have both the model code and the python Flask API working in a virtual environment in python on my computer. When I try to host the API on heroku, the code size exceeds the RAM limit. Are there any best practices for storing these models as static assets that can be called by an API? Is there a better way to do this to avoid hitting the RAM limit?
FYI: I used this tutorial for the model code - https://towardsdatascience.com/simple-abstractive-text-summarization-with-pretrained-t5-text-to-text-transfer-transformer-10f6d602c426 10