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 provenance/runtime.sha256 from anhdao69/SimpleMemVLN-R2R-RxR15deg-Window8-B: direct link, hf CLI and curl.
- Browser
- Download file 730 Bytes
-
https://huggingface.co/anhdao69/SimpleMemVLN-R2R-RxR15deg-Window8-B/resolve/main/provenance/runtime.sha256
- Command line
-
hf download hf://anhdao69/SimpleMemVLN-R2R-RxR15deg-Window8-B/provenance/runtime.sha256
-
curl -L -o runtime.sha256 https://huggingface.co/anhdao69/SimpleMemVLN-R2R-RxR15deg-Window8-B/resolve/main/provenance/runtime.sha256
730 Bytes
| 4870e12f937e7b7f281403a1f97042c9ad2b9f4c0b23d7b2eca3ba36536c6948 /mnt/data/vmo-ai-task/anhdh35/SimpleMemVLN/outputs/window8_text_2gpu_reportfix_20261002-xguUNX/deepspeed.json | |
| c0a5d5f4886ddc15ec44161d1ce9779a5e506efd454c730b56cf0059911429c3 /mnt/data/vmo-ai-task/anhdh35/SimpleMemVLN/outputs/window8_text_2gpu_reportfix_20261002-xguUNX/verify_two_gpu_profile.py | |
| 9f469d65fca4a82d3e0b14385aac7bfed12fb79c98e11a2a6db2073823cd5c86 /mnt/data/vmo-ai-task/anhdh35/SimpleMemVLN/outputs/window8_text_2gpu_reportfix_20261002-xguUNX/worst_manifest.jsonl | |
| b4222fd748e25130f4a8082ce0a351d64228be1f85f33fc7d1595ecfe4496e98 /mnt/data/vmo-ai-task/anhdh35/SimpleMemVLN/outputs/window8_text_2gpu_reportfix_20261002-xguUNX/window8_text_2gpu.slurm | |