If you enjoy this tool, please star this Gist! Author: fakerybakery (mrfakename). URL: https://gist.github.com/fakerybakery/df33cb8890da4ebf9e46f8a72e486f00
Heavily modified from: https://stackoverflow.com/a/18097502
Code:
function fgc($url) {
There appears to be a string encoded in the binary payload: | |
https://gist.github.com/q3k/af3d93b6a1f399de28fe194add452d01#file-hashes-txt-L115 | |
Which functions as a killswitch: | |
https://piaille.fr/@zeno/112185928685603910 | |
Thus, one workaround for affected systems might be to add this to `/etc/environment`: | |
``` |
XZ Backdoor symbol deobfuscation. Updated as i make progress |
""" To use: install LLM studio (or Ollama), clone OpenVoice, run this script in the OpenVoice directory | |
git clone https://github.com/myshell-ai/OpenVoice | |
cd OpenVoice | |
git clone https://huggingface.co/myshell-ai/OpenVoice | |
cp -r OpenVoice/* . | |
pip install whisper pynput pyaudio | |
""" | |
from openai import OpenAI | |
import time |
import copy | |
import os | |
import safetensors.torch | |
import glob | |
import json | |
def transform_st(path: str, out_dir: str): | |
data = safetensors.torch.load_file(path) | |
old_keys = list(data.keys()) |
{"task_id": "HumanEval/0", "prompt": "from typing import List\n\n\ndef has_close_elements(numbers: List[float], threshold: float) -> bool:\n \"\"\" Check if in given list of numbers, are any two numbers closer to each other than\n given threshold.\n >>> has_close_elements([1.0, 2.0, 3.0], 0.5)\n False\n >>> has_close_elements([1.0, 2.8, 3.0, 4.0, 5.0, 2.0], 0.3)\n True\n \"\"\"\n", "canonical_solution": " for idx, elem in enumerate(numbers):\n for idx2, elem2 in enumerate(numbers):\n if idx != idx2:\n distance = abs(elem - elem2)\n if distance < threshold:\n return True\n\n return False\n", "test": "\n\nMETADATA = {\n 'author': 'jt',\n 'dataset': 'test'\n}\n\n\ndef check(candidate):\n assert candidate([1.0, 2.0, 3.9, 4.0, 5.0, 2.2], 0.3) == True\n assert candidate([1.0, 2.0, 3.9, 4.0, 5.0, 2.2], 0.05) == False\n assert candidate([1.0, 2.0, 5.9, 4.0, 5.0], 0.95) == True\n assert candidate([1.0, 2.0, |
class AudioSessionManager: NSObject, ObservableObject { | |
@Published var microphones: [AVCaptureDevice] = [] | |
var captureSession: AVCaptureSession = .init() | |
var audioOutput: AVCaptureAudioDataOutput? | |
var configured: Bool = false | |
private var audioInput: AVCaptureDeviceInput? | |
let dataOutputQueue = DispatchQueue(label: "audio_queue", | |
qos: .userInteractive, |
""" | |
The code below combines approaches published by both @eugene-yh and @jinyongyoo on Github. | |
Thanks for the contributions guys! | |
""" | |
import torch | |
import peft |
# This script was adapted from merge.py from the KoboldAI discord server. | |
# I believe the original author is concedo | |
import os | |
import gc | |
import json | |
import shutil | |
import resource | |
import torch |
If you enjoy this tool, please star this Gist! Author: fakerybakery (mrfakename). URL: https://gist.github.com/fakerybakery/df33cb8890da4ebf9e46f8a72e486f00
Heavily modified from: https://stackoverflow.com/a/18097502
Code:
function fgc($url) {
name: 'Eric Venarusso' | |
age: '21' | |
sex: 'male' | |
sports: | |
- name: 'soccer' | |
team: | |
name: 'corinthians' | |
- name: 'basketball' |