Theia Vogel vgel

## _language_vector.py
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)

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

## readme.txt
Play this game by pasting the script in http://www.puzzlescript.net/editor.html

## readme.txt
Play this game by pasting the script in http://www.puzzlescript.net/editor.html

## readme.txt
Play this game by pasting the script in http://www.puzzlescript.net/editor.html

## tipping_gpt4.py
import os

import tqdm
import openai

openai.api_key = os.environ["OPENAI_API_KEY"]


def get_response(usermsg):
    response = openai.ChatCompletion.create(

## chunkpaper.py
# pip install beautifulsoup4 requests markdownify mistletoe

# command line usage: python chunkpaper.py 'https://ar5iv.org/abs/1910.06709'
# will dump the HTML, Markdown, and finally the chunk JSON
# note that (as of Nov 8 '23) ar5iv only has arxiv papers converted up to the end of October,
# but if you need something more recent you could probably do the LaTeX→HTML conversion yourself

# library usage: call `chunk` with some ar5iv HTML. will probably choke on anything else

import dataclasses

## _README.md

      
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                / _README.md
            
            
              Last active
              October 28, 2023 06:47
            
              
                Bantu Lexical Reconstructions 3 (Extracted from Filemaker Pro)
              
          
    Bantu Lexical Reconstructions 3

→ Browseable version with Datasette

Extracted from BLR, via their Filemaker database download.

  
## app.py
# put in rss_proxy/ as app.py and run with `python -m flask run`
# requirements: flask beautifulsoup4 requests lxml
# usage: `curl localhost:5000?feed=https://instance.example.com/users/username.rss`

from bs4 import BeautifulSoup
from flask import Flask, request
import requests
from lxml.builder import E
import lxml.etree

## index.html
<!DOCTYPE html>
<html>
<head>
  <meta charset="utf-8">
  <meta name="viewport" content="width=device-width">
  <title>JS Bin</title>
  <script src="https://cdnjs.cloudflare.com/ajax/libs/pixi.js/4.5.3/pixi.js"></script>
  <script src="https://cdnjs.cloudflare.com/ajax/libs/planck-js/0.1.34/planck-with-testbed.js"></script>
</head>
<body>
	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,
	import os

	import tqdm
	import openai

	openai.api_key = os.environ["OPENAI_API_KEY"]


	def get_response(usermsg):
	response = openai.ChatCompletion.create(
	# pip install beautifulsoup4 requests markdownify mistletoe

	# command line usage: python chunkpaper.py 'https://ar5iv.org/abs/1910.06709'
	# will dump the HTML, Markdown, and finally the chunk JSON
	# note that (as of Nov 8 '23) ar5iv only has arxiv papers converted up to the end of October,
	# but if you need something more recent you could probably do the LaTeX→HTML conversion yourself

	# library usage: call `chunk` with some ar5iv HTML. will probably choke on anything else

	import dataclasses
	# put in rss_proxy/ as app.py and run with `python -m flask run`
	# requirements: flask beautifulsoup4 requests lxml
	# usage: `curl localhost:5000?feed=https://instance.example.com/users/username.rss`

	from bs4 import BeautifulSoup
	from flask import Flask, request
	import requests
	from lxml.builder import E
	import lxml.etree
	<!DOCTYPE html>
	<html>
	<head>
	<meta charset="utf-8">
	<meta name="viewport" content="width=device-width">
	<title>JS Bin</title>
	<script src="https://cdnjs.cloudflare.com/ajax/libs/pixi.js/4.5.3/pixi.js"></script>
	<script src="https://cdnjs.cloudflare.com/ajax/libs/planck-js/0.1.34/planck-with-testbed.js"></script>
	</head>
	<body>