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# So you want to run GPT-J-6B using HuggingFace+FastAPI on a local rig (3090 or TITAN) ... tricky.
# special help from the Kolob Colab server https://colab.research.google.com/drive/1VFh5DOkCJjWIrQ6eB82lxGKKPgXmsO5D?usp=sharing#scrollTo=iCHgJvfL4alW
# Conversion to HF format (12.6GB tar image) found at https://drive.google.com/u/0/uc?id=1NXP75l1Xa5s9K18yf3qLoZcR6p4Wced1&export=download
# Uses GDOWN to get the image
# You will need 26 GB of space, 12+GB for the tar and 12+GB expanded (you can nuke the tar after expansion)

# Near Simplest Language model API, with room to expand!
# runs GPT-J-6B on 3090 and TITAN and servers it using FastAPI
# change "seq" (which is the context size) to adjust footprint

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import tensorflow as tf
from tqdm import tqdm

index = open("data/openwebtext2_new_inputs.train.index").read().splitlines()

dataset = tf.data.Dataset.from_tensor_slices(index)
dataset = dataset.interleave(tf.data.TFRecordDataset, cycle_length=128, num_parallel_calls=tf.data.experimental.AUTOTUNE)

d = dataset.shuffle(10000).prefetch(100)

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# refactor of https://lukeplant.me.uk/blog/posts/double-checked-locking-with-django-orm/
# untested

def double_checked_lock_iterator(queryset):
    for item_pk in queryset.values_list("pk", flat=True):
        with transaction.atomic():
            try:
                yield queryset.select_for_update(skip_locked=True).get(id=item_pk)
            except queryset.model.DoesNotExist:
                pass

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Project Title

One Paragraph of project description goes here

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.

Prerequisites

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$/
  artifacts/
  build/
  docs/
  lib/
  packages/
  samples/
  src/
 tests/

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const routes = {
  home: '/',
  transactions: '/transactions',
  transactionDetails: '/transactions/:uuid',
}

const urls: Record<
  keyof typeof routes,
  { get: (params?: any) => string; route: string }
> = new Proxy(routes, {

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# Sebastian Raschka 09/24/2022
# Create a new conda environment and packages
#   conda create -n whisper python=3.9
#   conda activate whisper
#   conda install mlxtend -c conda-forge

# Install ffmpeg
# macOS & homebrew
#   brew install ffmpeg
# Ubuntu

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Google Summer of Code 2022 Work Product

This document summarises the work that I have done as part of Google Summer of Code 2022 (GSoC).

Summary

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#!/usr/bin/env bash

# Small shell script to more easily automatically download and transcribe live stream VODs.
# This uses YT-DLP, ffmpeg and the CPP version of Whisper: https://github.com/ggerganov/whisper.cpp
# Use `./transcribe-vod help` to print help info.

# MIT License

# Copyright (c) 2022 Daniils Petrovs