pen.el
stable-baselines3-contrib
| pen.el | stable-baselines3-contrib | |
|---|---|---|
| 21 | 6 | |
| 465 | 427 | |
| - | 4.0% | |
| 9.5 | 6.7 | |
| over 1 year ago | about 1 month ago | |
| Emacs Lisp | Python | |
| GNU General Public License v3.0 only | MIT License |
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pen.el
- Pen.el – Emacs-based operating system designed with holiness in mind
- I turned my AI project into Bible software after getting born-again
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I wrote an Emacs package for ChatGPT
I'd like to also through https://github.com/semiosis/pen.el as an option. It integrates quite a few open source clients into emacs and can turn it into an "imaginary" editor of sorts
- pen.el: Pen.el stands for Prompt Engineering in emacs. Create, discover and use prompts to language models. Pen supports EleutherAI, Aleph-Alpha, HuggingFace
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Created a Twitter bot to ask for prompts and input the prompts from the replies and tweet out the results… bad idea lol
Why not use emacs?
- 'pen.el': a package for prompt engineering in emacs. (It facilitates the creation, ongoing development, discovery and usage of prompts to a language model such as OpenAI's GPT-3 or EleutherAI's GPT-j.)
- Imaginary programming with GPT-3/Codex
- I say, if GPT3 is this phenomenal, can you imagine how jaw dropping GPT69 is gonna be?
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Open call for an ELisp hacker to bring GitHub Copilot to Emacs (yes, really)
Sort of: Pen. https://github.com/semiosis/pen.el/
- Show HN: Pen.el (Working GPT-3/LM for Emacs with easy Docker install)
stable-baselines3-contrib
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Problem with Truncated Quantile Critics (TQC) and n-step learning algorithm.
# https://github.com/Stable-Baselines-Team/stable-baselines3-contrib/blob/master/sb3_contrib/tqc/tqc.py :
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Understanding Action Masking in RLlib
Here's a theoretical overview and an implementation of action masking for PPO.
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PPO rollout buffer for turn-based two-player game with varying turn lengths
Simplified version of rollout collection (adapted from ppo_mask.py line 282):
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GitHub Copilot: your AI pair programmer
Transformers (GPT-3) aren't quite _supervised_, but it does require valid samples.
Agree 100% with RL being the path forward. You probably have already seen ( https://venturebeat.com/2021/06/09/deepmind-says-reinforceme... ). Personally I'm really stoked for this https://github.com/Stable-Baselines-Team/stable-baselines3-c... , which will make it a lot easier for rubes like me to use RL.
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[P] Stable-Baselines3 v1.0 - Reliable implementations of RL algorithms
But as we already have vanilla DQN and QR-DQN (in our contrib repo: https://github.com/Stable-Baselines-Team/stable-baselines3-contrib ) I think it is already a good start for off-policy discrete action algorithms. (QR-DQN is usually competitive vs DQN+extensions)
What are some alternatives?
TabNine - AI Code Completions
muzero-general - MuZero
check-if-email-exists - Check if an email address exists without sending any email, written in Rust. Comes with a ⚙️ HTTP backend.
vim-plugin - The Kite plugin for Vim.
stable-baselines3-c
prompts - A free and open-source curation of prompts for OpenAI's GPT-3/Codex, EleutherAI's GPT-j, AlephAlpha's World Model and other language models.
copilot-cli - The AWS Copilot CLI is a tool for developers to build, release and operate production ready containerized applications on AWS App Runner or Amazon ECS on AWS Fargate.
asciinema - Terminal session recorder 📹
rl-baselines3-zoo - A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.
dreamerv2 - Mastering Atari with Discrete World Models