Reinforcement Learning
stable-baselines3
PandaReachDense-v3
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use abigail8n21/a2c-PandaReachDense-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use abigail8n21/a2c-PandaReachDense-v3 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="abigail8n21/a2c-PandaReachDense-v3", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download vec_normalize.pkl from abigail8n21/a2c-PandaReachDense-v3: direct link, hf CLI and curl.
- Browser
- Download file 2.65 kB
-
https://huggingface.co/abigail8n21/a2c-PandaReachDense-v3/resolve/main/vec_normalize.pkl
- Command line
-
hf download hf://abigail8n21/a2c-PandaReachDense-v3/vec_normalize.pkl
-
curl -L -o vec_normalize.pkl https://huggingface.co/abigail8n21/a2c-PandaReachDense-v3/resolve/main/vec_normalize.pkl
2.65 kB
- Xet hash:
- 485eb0309a3f61b992b6d6bd6f36ec28a2cedd929c40ab9d8ebc2fc0cb0129e8
- Size of remote file:
- 2.65 kB
- SHA256:
- c4e19f3647d2d49531b81ce20a53819866e723274bbe5c0e622012d61b26fcbd
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.