diff --git a/notebooks/bonus-unit1/bonus-unit1.ipynb b/notebooks/bonus-unit1/bonus-unit1.ipynb index 13deda7..1e02d4c 100644 --- a/notebooks/bonus-unit1/bonus-unit1.ipynb +++ b/notebooks/bonus-unit1/bonus-unit1.ipynb @@ -509,7 +509,7 @@ "\n", "This step is the simplest:\n", "\n", - "- Open the game Huggy in your browser: https://huggingface.co/spaces/ThomasSimonini/Huggy\n", + "- Open the game Huggy in your browser: https://singularite.itch.io/huggy\n", "\n", "- Click on Play with my Huggy model\n", "\n", @@ -569,4 +569,4 @@ }, "nbformat": 4, "nbformat_minor": 0 -} \ No newline at end of file +} diff --git a/units/en/unit0/introduction.mdx b/units/en/unit0/introduction.mdx index aba76dd..c0586c7 100644 --- a/units/en/unit0/introduction.mdx +++ b/units/en/unit0/introduction.mdx @@ -23,7 +23,7 @@ In this course, you will: - πŸ“– Study Deep Reinforcement Learning in **theory and practice.** - πŸ§‘β€πŸ’» Learn to **use famous Deep RL libraries** such as [Stable Baselines3](https://stable-baselines3.readthedocs.io/en/master/), [RL Baselines3 Zoo](https://github.com/DLR-RM/rl-baselines3-zoo), [Sample Factory](https://samplefactory.dev/) and [CleanRL](https://github.com/vwxyzjn/cleanrl). -- πŸ€– **Train agents in unique environments** such as [SnowballFight](https://huggingface.co/spaces/ThomasSimonini/SnowballFight), [Huggy the Doggo 🐢](https://huggingface.co/spaces/ThomasSimonini/Huggy), [VizDoom (Doom)](https://vizdoom.cs.put.edu.pl/)Β and classical ones such as [Space Invaders](https://www.gymlibrary.dev/environments/atari/), [PyBullet](https://pybullet.org/wordpress/) and more. +- πŸ€– **Train agents in unique environments** such as [SnowballFight](https://huggingface.co/spaces/ThomasSimonini/SnowballFight), [Huggy the Doggo 🐢](https://singularite.itch.io/huggy), [VizDoom (Doom)](https://vizdoom.cs.put.edu.pl/)Β and classical ones such as [Space Invaders](https://www.gymlibrary.dev/environments/atari/), [PyBullet](https://pybullet.org/wordpress/) and more. - πŸ’Ύ Share your **trained agents with one line of code to the Hub** and also download powerful agents from the community. - πŸ† Participate in challenges where you will **evaluate your agents against other teams. You'll also get to play against the agents you'll train.** diff --git a/units/en/unitbonus1/introduction.mdx b/units/en/unitbonus1/introduction.mdx index 68a57f9..c842bab 100644 --- a/units/en/unitbonus1/introduction.mdx +++ b/units/en/unitbonus1/introduction.mdx @@ -1,6 +1,6 @@ # Introduction [[introduction]] -In this bonus unit, we'll reinforce what we learned in the first unit by teaching Huggy the Dog to fetch the stick and then [play with him directly in your browser](https://huggingface.co/spaces/ThomasSimonini/Huggy) 🐢 +In this bonus unit, we'll reinforce what we learned in the first unit by teaching Huggy the Dog to fetch the stick and then [play with him directly in your browser](https://singularite.itch.io/huggy) 🐢 Unit bonus 1 thumbnail diff --git a/units/en/unitbonus1/play.mdx b/units/en/unitbonus1/play.mdx index f2154cc..4a17752 100644 --- a/units/en/unitbonus1/play.mdx +++ b/units/en/unitbonus1/play.mdx @@ -4,7 +4,7 @@ Now that you've trained Huggy and pushed it to the Hub. **You will be able to pl For this step it’s simple: -- Open the game Huggy in your browser: https://huggingface.co/spaces/ThomasSimonini/Huggy +- Open the game Huggy in your browser: https://singularite.itch.io/huggy - Click on Play with my Huggy model diff --git a/units/en/unitbonus1/train.mdx b/units/en/unitbonus1/train.mdx index 0ac738b..3cb1f1c 100644 --- a/units/en/unitbonus1/train.mdx +++ b/units/en/unitbonus1/train.mdx @@ -236,7 +236,7 @@ But now comes the best: **being able to play with Huggy online πŸ‘€.** This step is the simplest: -- Open the game Huggy in your browser: https://huggingface.co/spaces/ThomasSimonini/Huggy +- Open the game Huggy in your browser: https://singularite.itch.io/huggy - Click on Play with my Huggy model