Instructions to use anhdao69/SimpleMemVLN-R2R-RxR15deg-Window8-B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anhdao69/SimpleMemVLN-R2R-RxR15deg-Window8-B with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("anhdao69/SimpleMemVLN-R2R-RxR15deg-Window8-B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download epoch-1/pytorch_model.bin from anhdao69/SimpleMemVLN-R2R-RxR15deg-Window8-B: direct link, hf CLI and curl.
- Browser
- Download file 10.4 GB
-
https://huggingface.co/anhdao69/SimpleMemVLN-R2R-RxR15deg-Window8-B/resolve/main/epoch-1/pytorch_model.bin
- Command line
-
hf download hf://anhdao69/SimpleMemVLN-R2R-RxR15deg-Window8-B/epoch-1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/anhdao69/SimpleMemVLN-R2R-RxR15deg-Window8-B/resolve/main/epoch-1/pytorch_model.bin
10.4 GB
- Xet hash:
- 254df5bf23732610e3e42174e82992d21f107dadbf5740a302b3b4492f921dc3
- Size of remote file:
- 10.4 GB
- SHA256:
- e5c81d168326d59e6b48321fbd73da713b280a92dc2fcd0865e15aa8382f281e
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