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-2/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-2/pytorch_model.bin
- Command line
-
hf download hf://anhdao69/SimpleMemVLN-R2R-RxR15deg-Window8-B/epoch-2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/anhdao69/SimpleMemVLN-R2R-RxR15deg-Window8-B/resolve/main/epoch-2/pytorch_model.bin
10.4 GB
- Xet hash:
- 43330461bcfe914c2073324c7bec07d150f250a1bcf2e892a97952d35f2049d2
- Size of remote file:
- 10.4 GB
- SHA256:
- 4391b1f697616e2f003c0afbfed5f85327e4c2986d8922f73cd1a556bbf6dbcf
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