Reinforcement Learning
Transformers
PyTorch
decision_transformer
feature-extraction
deep-reinforcement-learning
decision-transformer
gym-continous-control
Instructions to use edbeeching/decision-transformer-gym-walker2d-medium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use edbeeching/decision-transformer-gym-walker2d-medium with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("edbeeching/decision-transformer-gym-walker2d-medium") model = AutoModel.from_pretrained("edbeeching/decision-transformer-gym-walker2d-medium", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from edbeeching/decision-transformer-gym-walker2d-medium: direct link, hf CLI and curl.
- Browser
- Download file 6.61 MB
-
https://huggingface.co/edbeeching/decision-transformer-gym-walker2d-medium/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://edbeeching/decision-transformer-gym-walker2d-medium/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/edbeeching/decision-transformer-gym-walker2d-medium/resolve/main/pytorch_model.bin
6.61 MB
- Xet hash:
- 5288e139f8019edd0d4d9cb6920db05c5a3617fdfb07c3f46425e8a3a6c0c44e
- Size of remote file:
- 6.61 MB
- SHA256:
- 6961bf64e04e67a1fe9872e9481bf7f380229ecb73bd79b7a613d17652c59c13
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.