veekaybee

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

biochem-fan

RELION interoperabiity with Warp and M

This document examines how to use RELION 4.0 (beta2 as of writing) with Warp 1.09 and M 1.09 for single particle analysis.

Special thanks to Alister Burt, Pranav Shah and Dimitry Tegunov for discussion on this Twitter thread.

Download the movies

We use the RELION tutorial dataset (beta-galactosidase collected on JEOL CRYO ARM 200, a subset of EMPIAR-10204).

InnovArul

import torchvision, copy
import torch, torch.nn as nn

def reset_all_weights(model: nn.Module) -> None:
    """
    refs:
        - https://discuss.pytorch.org/t/how-to-re-set-alll-parameters-in-a-network/20819/6
        - https://stackoverflow.com/questions/63627997/reset-parameters-of-a-neural-network-in-pytorch
        - https://pytorch.org/docs/stable/generated/torch.nn.Module.html
    """

dario2994

#!/usr/bin/env python3

# This program prints all hcn (highly composite numbers) <= MAXN (=10**18)
#
# The value of MAXN can be changed arbitrarily. When MAXN = 10**100, the
# program needs less than one second to generate the list of hcn.
from math import log

MAXN = 10**18