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/fine_tuned/seq2seq_plus/pytorch_model.bin from InternRobotics/VLN-PE: direct link, hf CLI and curl.
- Browser
- Download file 133 MB
-
https://huggingface.co/InternRobotics/VLN-PE/resolve/main/r2r/fine_tuned/seq2seq_plus/pytorch_model.bin
- Command line
-
hf download hf://InternRobotics/VLN-PE/r2r/fine_tuned/seq2seq_plus/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/InternRobotics/VLN-PE/resolve/main/r2r/fine_tuned/seq2seq_plus/pytorch_model.bin
133 MB
- Xet hash:
- 6f32b931218c70c35e84d26e571bd475dc64b4aa8e370d3965c3bcc37c1e6094
- Size of remote file:
- 133 MB
- SHA256:
- 1b510fc3e18a1f57cc714af9fc975dcb60eddfcf76aa51daae582bd864dbec4a
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