Reinforcement Learning
Transformers
PyTorch
decision_transformer
feature-extraction
deep-reinforcement-learning
decision-transformer
gym-continous-control
Instructions to use edbeeching/decision-transformer-gym-hopper-expert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use edbeeching/decision-transformer-gym-hopper-expert with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("edbeeching/decision-transformer-gym-hopper-expert") model = AutoModel.from_pretrained("edbeeching/decision-transformer-gym-hopper-expert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5fd5cadc5affb755b8ef0d23b995bbfa4bb4ffbe5714606fcb81cfcd1d92e7c8
- Size of remote file:
- 6.6 MB
- SHA256:
- 4c16a90bfc8bcca09a015021250df79d6d1450e85ac01b7ca5ac549318695893
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.