From 1f0edd7ddd229900eb970dabc393262055304ff7 Mon Sep 17 00:00:00 2001 From: Thomas Simonini Date: Wed, 3 May 2023 17:38:55 +0200 Subject: [PATCH] Add colab info --- units/en/unit4/hands-on.mdx | 11 +++++++++++ 1 file changed, 11 insertions(+) diff --git a/units/en/unit4/hands-on.mdx b/units/en/unit4/hands-on.mdx index 8a1a889..ea90f9a 100644 --- a/units/en/unit4/hands-on.mdx +++ b/units/en/unit4/hands-on.mdx @@ -37,6 +37,9 @@ And you can check your progress here 👉 https://huggingface.co/spaces/ThomasSi [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/huggingface/deep-rl-class/blob/master/notebooks/unit4/unit4.ipynb) +We strongly **recommend students use Google Colab for the hands-on exercises** instead of running them on their personal computers. + +By using Google Colab, **you can focus on learning and experimenting without worrying about the technical aspects** of setting up your environments. # Unit 4: Code your first Deep Reinforcement Learning Algorithm with PyTorch: Reinforce. And test its robustness 💪 @@ -134,6 +137,14 @@ The first step is to install the dependencies. We’ll install multiple ones: - `gym-games`: Extra gym environments made with PyGame. - `huggingface_hub`: The Hub works as a central place where anyone can share and explore models and datasets. It has versioning, metrics, visualizations, and other features that will allow you to easily collaborate with others. +You may be wondering why we install gym and not gymnasium, a more recent version of gym? **Because the gym-games we are using are not updated yet with gymnasium**. + +The differences you'll encounter here: +- In `gym` we don't have `terminated` and `truncated` but only `done`. +- In `gym` using `env.step()` returns `state, reward, done, info` + +You can learn more about the differences between Gym and Gymnasium here 👉 https://gymnasium.farama.org/content/migration-guide/ + You can see here all the Reinforce models available 👉 https://huggingface.co/models?other=reinforce And you can find all the Deep Reinforcement Learning models here 👉 https://huggingface.co/models?pipeline_tag=reinforcement-learning