Reinforcement Learning
Transformers
PyTorch
decision_transformer
feature-extraction
deep-reinforcement-learning
decision-transformer
gym-continous-control
Instructions to use edbeeching/decision-transformer-gym-hopper-medium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use edbeeching/decision-transformer-gym-hopper-medium with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("edbeeching/decision-transformer-gym-hopper-medium") model = AutoModel.from_pretrained("edbeeching/decision-transformer-gym-hopper-medium", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f9771ff10e46a47adc3e02c54ed6f753bd0e41ea34431fba5d54959bd2d6cca0
- Size of remote file:
- 6.6 MB
- SHA256:
- b753583ea04ec9ef07f986792e1572c9d757ffca00bd3d95a51a64454a7c057b
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