TabNine
stable-baselines3-contrib
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| TabNine | stable-baselines3-contrib | |
|---|---|---|
| 7 | 6 | |
| 10,387 | 427 | |
| 1.3% | 8.0% | |
| 0.0 | 6.7 | |
| 7 days ago | 29 days ago | |
| Shell | Python | |
| MIT License | MIT License |
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TabNine
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Tabnine ships new code-native AI models, passes 1 million developers using its AI code assistant
Other people complaining too: https://github.com/codota/TabNine/issues/179
- L'Italia è il primo paese dell'Unione Europea per percentuale di NEET (giovani che non studiano nè lavorano) - Cosa ne pensate?
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The Complete API Security Checklist
As applications grow in value to the end user so do they grow in complexity. Developers are pressured to increase productivity. Startups like Tabnine and Raycast have had impressive funding rounds recently, indicating how important developer productivity has become. With this pressure to perform, developers don't have the time to test each API connection for vulnerabilities or perform periodical penetration testing to ensure that new attack surfaces are not being introduced.
- GitHub Copilot Beta – My Experience
- GitHub Copilot: your AI pair programmer
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42 Companies using Rust in production
We also use rust to build Tabnine! (see https://tabnine.com)
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Tabnine links
Tabnine backend: https://github.com/codota/TabNine
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?
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.
muzero-general - MuZero
Flowgorithm-macOS - Flowgorithm for Mac OS
stable-baselines3-c
githut - Github Language Statistics
asciinema - Terminal session recorder 📹
rl-baselines3-zoo - A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.
pen.el - Pen.el stands for Prompt Engineering in emacs. It facilitates the creation, discovery and usage of prompts to language models. Pen supports OpenAI, EleutherAI, Aleph-Alpha, HuggingFace and others. It's the engine for the LookingGlass imaginary web browser.
dreamerv2 - Mastering Atari with Discrete World Models
AiDungeon2-Docker-ROCm - Runs an AIDungeon2 fork in Docker on AMD ROCm hardware.
robot-gym - RL applied to robotics.