Fabrizio Milo Mistobaan

A good way to get a taste of Swift for Tensorflow language and tools is to set it up with Jupyter with the fastai Swift notebooks. I wanted a quick setup, which the Mac install experience currently not, so instead I installed the release binaries in a Ubuntu container via Docker. The setup process for this scenario is not well documented, so here it is for you / future me.

What we're about to do is install the S4TF 0.4 release and the fastai v3 Swift notebooks on Ubuntu 18.04. Generally we follow the swift-jupyter docker file, but install cpu-only release versions of the packages.

Below are some of the references I looked at:

Rationale for S4TF and background reading

https://github.com/tensorflow/swift/blob/master/docs/WhySwiftForTensorFlow.md https://github.com/tensorflow/swift/blob/master/docs/DifferentiableFunctions.md

	# Example usage:
	# python merge_peft.py --base_model=meta-llama/Llama-2-7b-hf --peft_model=./qlora-out --hub_id=alpaca-qlora

	from transformers import AutoModelForCausalLM, AutoTokenizer
	from peft import PeftModel
	import torch

	import argparse

	def get_args():


	import base64
	import os
	import json
	import pickle
	import uuid
	import re

	import streamlit as st
	import pandas as pd

	import json
	from subprocess import check_output
	from time import sleep
	!pip -q install youtube-dl

	from google.colab import auth
	auth.authenticate_user()
	!gcloud config set project kora-id
	gcs = 'gs://co-lab/dhamma' # use your own project, gcs

	pip install streamlit
	pip install spacy
	python -m spacy download en_core_web_sm
	python -m spacy download en_core_web_md
	python -m spacy download de_core_news_sm

	pip install grpcio-tools

	wget https://github.com/tensorflow/tensorflow/archive/v1.9.0.zip -O tf-190.zip
	unzip tf-190.zip && rm tf-190.zip

	wget https://github.com/tensorflow/serving/archive/1.9.0.zip -O tf-serving-190.zip
	unzip tf-serving-190.zip && rm tf-serving-190.zip

	mv serving-1.9.0/tensorflow_serving tensorflow-1.9.0

	from google.cloud import storage
	from airflow.hooks.base_hook import BaseHook
	from airflow.utils.log.logging_mixin import LoggingMixin
	import random
	import string


	class GCSCustomHook(BaseHook, LoggingMixin):

	def __init__(self, storage_conn_id='google_cloud_storage_default'):