Reinforcement Learning
stable-baselines3
PandaReachDense-v2
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use 1daniar/a2c-PandaReachDense-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use 1daniar/a2c-PandaReachDense-v2 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="1daniar/a2c-PandaReachDense-v2", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download vec_normalize.pkl from 1daniar/a2c-PandaReachDense-v2: direct link, hf CLI and curl.
- Browser
- Download file 2.46 kB
-
https://huggingface.co/1daniar/a2c-PandaReachDense-v2/resolve/main/vec_normalize.pkl
- Command line
-
hf download hf://1daniar/a2c-PandaReachDense-v2/vec_normalize.pkl
-
curl -L -o vec_normalize.pkl https://huggingface.co/1daniar/a2c-PandaReachDense-v2/resolve/main/vec_normalize.pkl
2.46 kB
- Xet hash:
- 812a9d2ccc9d2e579638425714443b5ea61752b2979db7177588ac2cfbb59fe1
- Size of remote file:
- 2.46 kB
- SHA256:
- fa905cb3ee1b721cd901bd605dd03066ef2150473acb468c7126f6843aaaa6ec
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.