Max Azoury CoolOppo

Minimal Prompt Chainables

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

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

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:

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.

Make sure the following options are off:

	// Updated: Aug. 20, 2024
	// Run: node testRegex.js whatever.txt
	// Live demo: https://jina.ai/tokenizer
	// LICENSE: Apache-2.0 (https://www.apache.org/licenses/LICENSE-2.0)
	// COPYRIGHT: Jina AI
	const fs = require('fs');
	const util = require('util');

	// Define variables for magic numbers
	const MAX_HEADING_LENGTH = 7;

	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],

	# 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

	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)

	➜ 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***