ossa-ma

---

name: the writing whip description: >- Kill all AI writing tropes and behaviours at the source: generation. Focus on quelling behaviour-driven triggers. Load before writing, especially for anything longer than a paragraph and re-check output against it, extremely important for communications, documentation, outbound, client-facing copy and for your own replies to the user. metadata: category: writing author: Ossama Chaib

agokrani

'system': 
[
  {
     'type': 'text', 
     'text': "You are Claude Code, Anthropic's official CLI for Claude.", 
     'cache_control': {'type': 'ephemeral'}
  }, 
  {
     'type': 'text',
     'text': 'You are an interactive CLI tool that helps users with software engineering tasks. 

disler

Minimal Prompt Chainables

Sequential prompt chaining in one method with context and output back-referencing.

Files

• main.py - start here - full example using MinimalChainable from chain.py to build a sequential prompt chain
• chain.py - contains zero library minimal prompt chain class
• chain_test.py - tests for chain.py, you can ignore this
• requirements.py - python requirements

Setup

0xdevalias

Deobfuscating / Unminifying Obfuscated Web App / JavaScript Code

Some notes and tools for reverse engineering / deobfuscating / unminifying obfuscated web app code.

Table of Contents

• tl;dr: AKA: devalias's shortlist
• PoC
• Benchmarks / Leaderboards / etc

TheBloke

import time
import os
import logging
import random
from datasets import load_dataset

class QuantAutoGPTQ:
    def __init__(self, model_name_or_path, output_dir, dataset,
                 num_samples=128, trust_remote_code=False, cache_examples=True,
                 use_fast=True, use_triton=False, bits=[4], group_size=[128], damp=[0.01],

pacman100

# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software

TheBloke

from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel
import torch

import os
import argparse

def get_args():
    parser = argparse.ArgumentParser()
    parser.add_argument("--base_model_name_or_path", type=str)

dzoba

➜  babyagi git:(main) python3.9 babyagi.py

*****OBJECTIVE*****

I have been given no context other than I am an agent existing in a universe. Why am I here? I do not know.  I must discover my own objective.

Initial task: Begin

*****TASK LIST*****

YuRaNnNzZZ

All base documentation has moved to it's own GitHub repo: https://github.com/YuRaNnNzZZ/TFA-SWEP-Base-Documentation

This Gist will not be updated anymore.

This is the official TFA SWEP Base documentation.

Before going through anything from here, make sure you have read through Lua basics guide for GMod here first!

List of contents:

Myndex

What's Up With Markdown

GitHub Flavored Markdown Cheat Sheet

This serves as a quick reference and showcase of GitHub Flavored Markdown. For more complete info, see John Gruber's original spec and the Github-flavored Markdown info page.

Table of Contents