Jeff Triplett jefftriplett

Using Whisper to transcribe audio

This episode of Recsperts was transcribed with Whisper from OpenAI, an open-source neural net trained on almost 700 hours of audio. The model includes an encoder-decoder architecture by tokenizing audio into 30-second chunks, normalizing audio samples to the log-Mel scale, and passing the data into an encoder. A decoder is trained to predict the captioned text matching the encoder, and the model includes transcription, as well as timestamp-aligned transcription, and multilingual translation.

The transcription process outputs a single string file, so it's up to the end-user to parse out individual speakers, or run the model [through a sec

ChatGPT Resources

Context

ChatGPT appeared like an explosion on all my social media timelines in early December 2022. While I keep up with machine learning as an industry, I wasn't focused so much on this particular corner, and all the screenshots seemed like they came out of nowhere. What was this model? How did the chat prompting work? What was the context of OpenAI doing this work and collecting my prompts for training data?

I decided to do a quick investigation. Here's all the information I've found so far. I'm aggregating and synthesizing it as I go, so it's currently changing pretty frequently.

Model Architecture

GitHub for code
Render blueprint specified by render.yaml
- Postgres
- Redis
- Linked to GitHub repo
- Add environment variables for PYTHON_VERISON=3.9.7, ENVIRONMENT=live, and SECRET_KEY
Cloudflare for SSL and CNAME pointing to Render app domain
- Force SSL with a Cloudflare rule
Namecheap for the domain
Point nameservers to Cloudflare

Why?

I got sick of writing the same Serializer & ModelViewSet classes over and over so I found and wrote some code to do it for me, and somehow it works! Please note that there are a lot of caveats to running an API like this and while this may work, I know there's A LOT of room for improvement, feel free to fork and help!

USAGE

Import the router module to your main sites urls.py file as the injection point like so... Make sure to remove any other imports from other viewsets that you don't need that may conflict!

	-i https://pypi.org/simple
	anyio==3.6.2; python_full_version >= '3.6.2'
	certifi==2022.12.7; python_version >= '3.6'
	click==8.1.3; python_version >= '3.7'
	colorama==0.4.6
	commonmark==0.9.1
	h11==0.14.0; python_version >= '3.7'
	httpcore==0.16.3; python_version >= '3.7'
	httpx==0.23.1
	idna==3.4

	#!/usr/bin/env python

	import argparse
	import os
	import subprocess
	import sys
	import time

	# Required so we don't generate tons of logs during restore
	disable_logging_sql = "ALTER USER postgres RESET pgaudit.log;"

	// service worker
	self.addEventListener("install", (event) => {
	event.waitUntil(
	caches.open("{{ cache_key }}").then((cache) =>
	cache.addAll([
	// {% for asset in assets %}
	"{{ asset }}",
	// {% endfor %}
	])
	)

	"""Find the earliest available version of a list of Python dependencies.

	This takes dependencies on the command line (package names with or without
	version specifiers), looks up each in PyPI, and outputs a new list of
	dependencies that specify the earliest version in each range.

	See https://twitter.com/simonw/status/1473441058667130881 for the reason for
	this script.

	Example:

	spec:
	containers:
	-
	name: misc
	image: gladiatr72/misc:util-21
	env:
	-
	name: POD_IP
	valueFrom:
	fieldRef:

	twitter.com##[aria-label$="Trending now" i]
	twitter.com##article [aria-label^="Recommended Topic" i]:upward(article)