Stefan Schweter stefan-it

CVE-2022-23812

RIAEvangelist/node-ipc is malware / protestware

The RIAEvangelist/node-ipc module contains protestware peacenotwar.

Excerpt from RIAEvangelist/node-ipc:

as of v11.0.0 & v9.2.2 this module uses the peacenotwar module.

Betreff: Berechtigungszertifikat für NPA An: [email protected]

Text: Sehr geehrte Damen und Herren, ich bin am Erwerb eines Berechtigungszertifikats für den neuen Personalausweis interessiert. Können Sie mir bitte ihre aktuelle Preisliste zukommen lassen?

Vielen Dank & viele Grüße,

[NAME]

A criticism of "On the Dangers of Stochastic Parrots: Can Languae Models be Too Big"

Yoav Goldberg, Jan 23, 2021.

The FAccT paper "On the Dangers of Stochastic Parrots: Can Languae Models be Too Big" by Bender, Gebru, McMillan-Major and Shmitchell has been the center of a controversary recently. The final version is now out, and, owing a lot to this controversary, would undoubtly become very widely read. I read an earlier draft of the paper, and I think that the new and updated final version is much improved in many ways: kudos for the authors for this upgrade. I also agree with and endorse most of the content. This is important stuff, you should read it.

However, I do find some aspects of the paper (and the resulting discourse around it and around technology) to be problematic. These weren't clear to me when initially reading the first draft several months ago, but they became very clear to me now. These points are for the most part

	# /// script
	# requires-python = ">=3.11,<3.12"
	# dependencies = [
	# "duckdb", sentence-transformers, huggingface_hub
	# ]
	# ///
	from sentence_transformers import SentenceTransformer
	import duckdb
	from huggingface_hub import get_token

	from transformers import ElectraForMaskedLM, ElectraForPreTraining
	from transformers.models.electra.modeling_electra import ElectraForPreTrainingOutput
	from torch import Tensor
	import torch.nn.functional as F
	import torch.nn as nn
	import torch


	class ElectraModel(nn.Module):
	def __init__(self,

	# See https://gist.github.com/BramVanroy/f78530673b1437ed0d6be7c61cdbdd7c
	parser = HfArgumentParser((ModelArguments, DataTrainingArguments, TrainingArguments, HyperOptArguments))

	try:
	# Assumes that the first .json file is the config file (if any)
	config_file = next(iter(arg for arg in sys.argv if arg.endswith(".json")))
	except StopIteration:
	config_file = None

	run_name_specified = False

	#!/usr/bin/env python3

	"""
	Example of a generic Mixout implementation. (Lee et al., 2019).
	https://arxiv.org/abs/1909.11299

	Implementation by Stephen Roller (https://stephenroller.com).

	Updated 2020-02-10 to include 1/(1 - p) correction term. Thanks to
	Cheolhyoung Lee for making this correction.

	# Copyright (c) 2019-present, Thomas Wolf.
	# All rights reserved. This source code is licensed under the MIT-style license.
	""" A very small and self-contained gist to train a GPT-2 transformer model on wikitext-103 """
	import os
	from collections import namedtuple
	from tqdm import tqdm
	import torch
	import torch.nn as nn
	from torch.utils.data import DataLoader
	from ignite.engine import Engine, Events


	; <<>> DiG 9.16.21 <<>> axfr 219.185.195.in-addr.arpa @91.189.192.6
	;; global options: +cmd
	; Transfer failed.