Instructions to use InternRobotics/VLN-PE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use InternRobotics/VLN-PE with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("InternRobotics/VLN-PE", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download r2r/zero_shot/cma/pytorch_model.bin from InternRobotics/VLN-PE: direct link, hf CLI and curl.
- Browser
- Download file 148 MB
-
https://huggingface.co/InternRobotics/VLN-PE/resolve/main/r2r/zero_shot/cma/pytorch_model.bin
- Command line
-
hf download hf://InternRobotics/VLN-PE/r2r/zero_shot/cma/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/InternRobotics/VLN-PE/resolve/main/r2r/zero_shot/cma/pytorch_model.bin
148 MB
- Xet hash:
- 6bacc2f25173a63f00e1865651069fc7ecb1f2e5dc2a3de3c98a199ec2d2fb8c
- Size of remote file:
- 148 MB
- SHA256:
- 693259a1e8d426c64573bbc838e430dba0e57cbe2e2b8d9a14b3b80e8c4fd448
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