Rohan Singh ygivenx

## normcore-llm.md

      
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                Normcore LLM Reads
              
          
    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


## h1b_telegram_alert.py
"""
Author: Rohan Singh (singhrohan@outlook.com)

Use this code to send yourself a message when a relevant one appears in the `group_name`
Also, get notifications on mac

Usage
===========

Go to: https://my.telegram.org to create an app

## roam2tex.js
/*
Input: Roam Research's non-standard markdown. (copied from a roam page or export)
Output: Latex

The goal of this is to draft papers and other documents in Roam.
Thus, we export regular text, *not* a bullet list!

Reads from stdin, writes to stdout.

Example input: https://roamresearch.com/#/app/publicpages/page/WP7tXRTgK

## forecasting_metrics.py
import numpy as np

EPSILON = 1e-10


def _error(actual: np.ndarray, predicted: np.ndarray):
    """ Simple error """
    return actual - predicted
	"""
	Author: Rohan Singh (singhrohan@outlook.com)

	Use this code to send yourself a message when a relevant one appears in the `group_name`
	Also, get notifications on mac

	Usage
	===========

	Go to: https://my.telegram.org to create an app
	/*
	Input: Roam Research's non-standard markdown. (copied from a roam page or export)
	Output: Latex

	The goal of this is to draft papers and other documents in Roam.
	Thus, we export regular text, not a bullet list!

	Reads from stdin, writes to stdout.

	Example input: https://roamresearch.com/#/app/publicpages/page/WP7tXRTgK
	import numpy as np

	EPSILON = 1e-10


	def _error(actual: np.ndarray, predicted: np.ndarray):
	""" Simple error """
	return actual - predicted