This is my constantly updated CS:GO autoexec config. Changelogs can be found under revisions here
Put autoexec.cfg in ...\Steam\steamapps\common\Counter-Strike Global Offensive\csgo\cfg or take what you want from it and add to your autoexec config!
After the Wild West Simulator 2015 update, video.txt needs to be put in ...\Steam\userdata\<Steam3 ID>\730\local\cfg
| import os | |
| from keras import backend as K | |
| from keras import callbacks | |
| from keras import layers | |
| from keras import models | |
| from keras.wrappers.scikit_learn import KerasClassifier | |
| import pandas as pd | |
| import tensorflow as tf | |
| from sklearn import metrics |
Yoav Goldberg, April 2023.
With the release of the ChatGPT model and followup large language models (LLMs), there was a lot of discussion of the importance of "RLHF training", that is, "reinforcement learning from human feedback". I was puzzled for a while as to why RL (Reinforcement Learning) is better than learning from demonstrations (a.k.a supervised learning) for training language models. Shouldn't learning from demonstrations (or, in language model terminology "instruction fine tuning", learning to immitate human written answers) be sufficient? I came up with a theoretical argument that was somewhat convincing. But I came to realize there is an additional argumment which not only supports the case of RL training, but also requires it, in particular for models like ChatGPT. This additional argument is spelled out in (the first half of) a talk by John Schulman from OpenAI. This post pretty much
