Instructions to use miiwater/goi-rl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use miiwater/goi-rl with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="miiwater/goi-rl", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -14,7 +14,7 @@ tags:
|
|
| 14 |
**The first reinforcement learning agent to finish the whole game in one continuous run.** A network by krzim
|
| 15 |
([GitHub](https://github.com/krzim), [Hugging Face](https://huggingface.co/zimmerk4)), trained in a JAX simulator of
|
| 16 |
the game, climbs the real Steam game from bottom to top with no save/load: 17 of 20 wins in krzim's test. Below, one
|
| 17 |
-
of its wins (
|
| 18 |
|
| 19 |
<video controls src="https://huggingface.co/miiwater/goi-rl/resolve/main/videos/krzim-network-wins.mp4"></video>
|
| 20 |
|
|
|
|
| 14 |
**The first reinforcement learning agent to finish the whole game in one continuous run.** A network by krzim
|
| 15 |
([GitHub](https://github.com/krzim), [Hugging Face](https://huggingface.co/zimmerk4)), trained in a JAX simulator of
|
| 16 |
the game, climbs the real Steam game from bottom to top with no save/load: 17 of 20 wins in krzim's test. Below, one
|
| 17 |
+
of its wins (1 min 35 s); the circle in the corner is its mouse input.
|
| 18 |
|
| 19 |
<video controls src="https://huggingface.co/miiwater/goi-rl/resolve/main/videos/krzim-network-wins.mp4"></video>
|
| 20 |
|