Instructions to use anhdao69/SimpleMemVLN-R2R-RxR15deg-FullContext-B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anhdao69/SimpleMemVLN-R2R-RxR15deg-FullContext-B with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("anhdao69/SimpleMemVLN-R2R-RxR15deg-FullContext-B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download epoch-2/pytorch_model.bin from anhdao69/SimpleMemVLN-R2R-RxR15deg-FullContext-B: direct link, hf CLI and curl.
- Browser
- Download file 10.4 GB
-
https://huggingface.co/anhdao69/SimpleMemVLN-R2R-RxR15deg-FullContext-B/resolve/main/epoch-2/pytorch_model.bin
- Command line
-
hf download hf://anhdao69/SimpleMemVLN-R2R-RxR15deg-FullContext-B/epoch-2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/anhdao69/SimpleMemVLN-R2R-RxR15deg-FullContext-B/resolve/main/epoch-2/pytorch_model.bin
10.4 GB
- Xet hash:
- 83660adae6441e6a80de053a597d0c7957fd1fe7e791abefa93f7a981379a21f
- Size of remote file:
- 10.4 GB
- SHA256:
- 0473596aef30e4bcbcd2c3fed0b5fd0e2f0324c1f6e949a926ad197a863fe72f
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