- Full screen browser
class ClassTest extends \PHPUnit_Extensions_Selenium2TestCase
{
public static $browsers = array(
array(| # Follow instructions here: http://flask.pocoo.org/snippets/65/ | |
| # You'll need to make sure you have the right Python version and any packages installed: http://docs.webfaction.com/software/python.html | |
| # This tweak to index.py is what made it actually work: http://stackoverflow.com/questions/3696606/how-to-solve-import-errors-while-trying-to-deploy-flask-using-wsgi-on-apache2 | |
| import sys | |
| yourappname = "/home/username/webapps/yourappname/htdocs" | |
| if not yourappname in sys.path: | |
| sys.path.insert(0, yourappname) | |
| from yourappname import app as application |
##VGG19 model for Keras
This is the Keras model of the 19-layer network used by the VGG team in the ILSVRC-2014 competition.
It has been obtained by directly converting the Caffe model provived by the authors.
Details about the network architecture can be found in the following arXiv paper:
Very Deep Convolutional Networks for Large-Scale Image Recognition
K. Simonyan, A. Zisserman
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