Instructions to use anhdao69/SimpleMemVLN-R2R-RxR15deg-FullContext-CandidateLogits with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anhdao69/SimpleMemVLN-R2R-RxR15deg-FullContext-CandidateLogits with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("anhdao69/SimpleMemVLN-R2R-RxR15deg-FullContext-CandidateLogits", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download manifest.sha256 from anhdao69/SimpleMemVLN-R2R-RxR15deg-FullContext-CandidateLogits: direct link, hf CLI and curl.
- Browser
- Download file 150 Bytes
-
https://huggingface.co/anhdao69/SimpleMemVLN-R2R-RxR15deg-FullContext-CandidateLogits/resolve/main/manifest.sha256
- Command line
-
hf download hf://anhdao69/SimpleMemVLN-R2R-RxR15deg-FullContext-CandidateLogits/manifest.sha256
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curl -L -o manifest.sha256 https://huggingface.co/anhdao69/SimpleMemVLN-R2R-RxR15deg-FullContext-CandidateLogits/resolve/main/manifest.sha256
150 Bytes
| 5deb425d2594ce96931dd6ce12bd6084b066cd44f04808c1dd3ee2e4b3672933 /mnt/data/vmo-ai-task/anhdh35/SimpleMemVLN/artifacts/r2r_rxr15_train_20260929.jsonl | |