Theia Vogel vgel

From the Benignitas, in Léon de Kerval’s 1904 edition, Sancti Antonii de Padua Vitæ Duæ, pp. 219-222, available at https://ia800205.us.archive.org/34/items/sanctiantoniide01kervgoog/sanctiantoniide01kervgoog.pdf

Notes:

Assidua (1232): Bononillo converted in Rimini by argument alone. No mule.
- “Among these, there was a heretic by the name of Bononillo who was for thirty years seduced by error into disbelief. Through his servant Anthony, the Lord brought him back to the path of truth. Once he accepted to do penance, he devoutly obeyed the commandments of the Holy Roman Church until the end.”
- Life of St. Anthony, "Assidua", p. 13, https://archive.org/details/lifeofstanthonya0000unse_h0q0/page/13/mode/1up?q=mule
Benignitas (14th c.): Mule miracle in Toulouse with an unnamed heretic. Explicitly distinguishes this from the Bononillo conversion.
- OCR'd and translated by Claude Opus 4.5 below, may have errors.

	# /// script
	# dependencies = [ "transformers", "accelerate" ]
	# ///

	# run on 2xH200 rented from primeintellect.ai

	import gc

	import torch
	from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer

	// curl -H "Authorization: Bearer ..." "https://$BASE_URL/models/features"
	{
	"host_fingerprint": "provider", // should be a unique string for the host or router (e.g. deepseek, openrouter, litellm)
	"data": [
	{
	// Required
	"id": "provider/model",
	"name": "Provider: Model",
	// should either match host_fingerprint if this is a primary provider (ie deepseek) or match the host_fingerprint of
	// the upstream provider, if this is a router. i.e., this string should never be "litellm"

	import math
	import os

	from openai import OpenAI
	from dotenv import load_dotenv

	load_dotenv()

	question = "Generate a random string of the letters A and B, no talk just go."
	model1, client1 = "gpt-4o-mini", OpenAI()

	import argparse
	import random
	import sys

	from transformers import AutoModelForCausalLM, AutoTokenizer, DynamicCache
	import torch

	parser = argparse.ArgumentParser()
	parser.add_argument("question", type=str)
	parser.add_argument(

	system: \|
	Assistant is acting as a helpful reference. The user is asking the given question through a command line interface and needs a concise answer. The interface does not support markdown, so the response should be plaintext. The response should be as concise as possible while still answering the question. For example, if the question is about the appropriate command to perform an action, the response should be just the command and nothing else. If the question is about a Python feature, the response should be just a code snippet, perhaps with a single-line explanatory comment if necessary--but assume the user is an expert and will ask clarifying questions if needed.

	# Examples

	Human: how do i write a for-loop in bash?
	Assistant: $bash_command

	Human: python mro lookup order
	Assistant: # depth first, then left to right

	import json

	import torch
	from transformers import AutoModelForCausalLM, AutoTokenizer

	from repeng import ControlVector, ControlModel, DatasetEntry

	model_name = "mistralai/Mistral-7B-Instruct-v0.1"

	tokenizer = AutoTokenizer.from_pretrained(model_name)

	[
	{
	"model": "34m",
	"index": 6426,
	"desc": "Grove startup; Gateway cloning technology",
	"usable": true
	},
	{
	"model": "34m",
	"index": 19443,