Instructions to use anhdao69/SimpleMemVLN-R2R-FullContext-B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anhdao69/SimpleMemVLN-R2R-FullContext-B with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("anhdao69/SimpleMemVLN-R2R-FullContext-B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download run_timing.json from anhdao69/SimpleMemVLN-R2R-FullContext-B: direct link, hf CLI and curl.
- Browser
- Download file 227 Bytes
-
https://huggingface.co/anhdao69/SimpleMemVLN-R2R-FullContext-B/resolve/main/run_timing.json
- Command line
-
hf download hf://anhdao69/SimpleMemVLN-R2R-FullContext-B/run_timing.json
-
curl -L -o run_timing.json https://huggingface.co/anhdao69/SimpleMemVLN-R2R-FullContext-B/resolve/main/run_timing.json
227 Bytes
| { | |
| "wall_seconds_including_load_and_save": 23922.57332988456, | |
| "trainer_runtime_seconds": 23890.122, | |
| "profile_only": false, | |
| "update_timer_note": "Update callbacks exclude loader prefetch and model load/checkpoint save" | |
| } | |