veekaybee

Anti-hype LLM reading list

Goals: Add links that are reasonable and good explanations of how stuff works. No hype and no vendor content if possible. Practical first-hand accounts of models in prod eagerly sought.

Foundational Concepts

Pre-Transformer Models

younesbelkada

# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software

svpino

Running TensorFlow on Apple Silicon

1. Install Homebrew The Missing Package Manager for macOS (or Linux) — Homebrew

2. Download Miniforge3

3. Install Miniforge3 and restart your terminal as soon as the installation finishes:

maslychm

Install PyTorch 1.12.0 with Mac M1 GPU support (MPS device: for Metal Performance Shaders)

TLDR: Dowload package directly from anaconda.org and install over the current torch version

Explanation

Wrong version (1.10.2) gets installed for me when I run conda install pytorch -c pytorch-nightly.
To fix, install the latest pytorch version from the stable channel, then manually download package for your python version, and install it over the current pytorch. Newest Pytorch Nightly releases here: Anaconda: Pytorch Nightly Files.

ortegatron

from detectron2.engine.hooks import HookBase
from detectron2.evaluation import inference_context
from detectron2.utils.logger import log_every_n_seconds
from detectron2.data import DatasetMapper, build_detection_test_loader
import detectron2.utils.comm as comm
import torch
import time
import datetime

class LossEvalHook(HookBase):

ylashin

import flask
from flask_cors import CORS
from flask import request, jsonify
from detectron2.engine import DefaultPredictor
from detectron2.config import get_cfg
from detectron2.data import MetadataCatalog
import cv2
import requests
import numpy as np

swedishmike

## Create the virtual environment
conda create -n 'environment_name'

## Activate the virtual environment
conda activate 'environment_name'

## Make sure that ipykernel is installed
pip install --user ipykernel

## Add the new virtual environment to Jupyter

MuhsinFatih

I am assuming you are here because like me, you installed a bazillion different python interpreters on mac and the whole thing is a spagetti. Today, I finally fixed my python installation. Whatever I install for python2 or python3 using pip JUST.WORKS.. My god! finally.

What the hell?

Here is what I had messed up, which you also probably did:

• I had too many different python interpreters
• Too many different symlinks which I lost track of
• almost no package I installed with pip worked without a headache
• any attempt to fix using online resources made it worse.

mschae16

To prepare for the Docker 101 workshop, please install Docker and follow the steps in creating a Dockerhub account.

To prepare for the Kubernetes 101 workshop, please install the following:

• Docker
• minikube

Verify your minikube install by running the following commands in your terminal:

$ minikube start and

aprilmintacpineda

How to follow this guide

• Don't type or run anything until I told you so.
• This guide uses linux commands. For windows users, you can use win-bash
  • https://sourceforge.net/projects/win-bash/files/shell-complete/latest/
  • http://win-bash.sourceforge.net/

The problem

I have one computer and two different github accounts. One is for work, the other is for my personal stuff. I can't use the same ssh key twice, so I have to use different ssh key for each of my accounts. How do I do that? How do I switch between these ssh keys?