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 SHA256SUMS.json from anhdao69/SimpleMemVLN-R2R-RxR15deg-Window8-B: direct link, hf CLI and curl.
- Browser
- Download file 2.46 kB
-
https://huggingface.co/anhdao69/SimpleMemVLN-R2R-RxR15deg-Window8-B/resolve/main/SHA256SUMS.json
- Command line
-
hf download hf://anhdao69/SimpleMemVLN-R2R-RxR15deg-Window8-B/SHA256SUMS.json
-
curl -L -o SHA256SUMS.json https://huggingface.co/anhdao69/SimpleMemVLN-R2R-RxR15deg-Window8-B/resolve/main/SHA256SUMS.json
2.46 kB
| { | |
| "README.md": "32cb1394c616aa117dd272d3c4ff5f6743fc048f879f90cddf4e4ebec2a023bd", | |
| "epoch-1/chat_template.jinja": "a4aee8afcf2e0711942cf848899be66016f8d14a889ff9ede07bca099c28f715", | |
| "epoch-1/config.json": "2451a8786918f4c348acb32c438d9a127098c022334ae1a7713ce5be588a7df1", | |
| "epoch-1/navigation.json": "eb16442ac04a6e0abf11bed2e3a079c779a9fbfde73e81c61cde09aa7e004424", | |
| "epoch-1/processor_config.json": "d89ef49ce9cd37fbf510158e13c1ef063d9286411c1ec9049932dbe0487143b1", | |
| "epoch-1/pytorch_model.bin": "e5c81d168326d59e6b48321fbd73da713b280a92dc2fcd0865e15aa8382f281e", | |
| "epoch-1/tokenizer.json": "06b9509352d2af50381ab2247e083b80d32d5c0aba91c272ca9ff729b6a0e523", | |
| "epoch-1/tokenizer_config.json": "7488550a894dcf741616126e322ea31d66cf9457b59ec5825f4c7efdced421f8", | |
| "epoch-1/trainer_state.json": "473f0838b9ef77697269bbc4a3deac1bff1b7062fd1cd211640d40b4e35b035b", | |
| "epoch-2/chat_template.jinja": "a4aee8afcf2e0711942cf848899be66016f8d14a889ff9ede07bca099c28f715", | |
| "epoch-2/config.json": "2451a8786918f4c348acb32c438d9a127098c022334ae1a7713ce5be588a7df1", | |
| "epoch-2/navigation.json": "eb16442ac04a6e0abf11bed2e3a079c779a9fbfde73e81c61cde09aa7e004424", | |
| "epoch-2/processor_config.json": "d89ef49ce9cd37fbf510158e13c1ef063d9286411c1ec9049932dbe0487143b1", | |
| "epoch-2/pytorch_model.bin": "4391b1f697616e2f003c0afbfed5f85327e4c2986d8922f73cd1a556bbf6dbcf", | |
| "epoch-2/tokenizer.json": "06b9509352d2af50381ab2247e083b80d32d5c0aba91c272ca9ff729b6a0e523", | |
| "epoch-2/tokenizer_config.json": "7488550a894dcf741616126e322ea31d66cf9457b59ec5825f4c7efdced421f8", | |
| "epoch-2/trainer_state.json": "7006fca79df16e1dee3983e3d770aeac9fd23fc3ca616168daa4657b5112f5bc", | |
| "provenance/deepspeed.json": "4870e12f937e7b7f281403a1f97042c9ad2b9f4c0b23d7b2eca3ba36536c6948", | |
| "provenance/manifest.sha256": "b679ab7ddb7e1a7af197d1598ac2253edb3624644136504d4f25ae575db8212f", | |
| "provenance/provenance-reportfix.json": "e49e52ddd3270d4b4990fc9bb09ca51be3ad0e1bba88d39274e6b5315fca456d", | |
| "provenance/runtime.sha256": "9cd9e1bf6e2b0f4b5c43af117779a38d0624d506099e9b1f2a606ef4d4312420", | |
| "provenance/source.sha256": "8969a2a67c97052e0322f8c726dbc7dafad1a63fe2bf6b078a792f3e130a6cec", | |
| "reports/epoch-1.json": "e5d2782f8358cc276160bfb7cb8502a96be2ad386f1d3aaea65c87da67c0d4d2", | |
| "reports/epoch-2.json": "70055f4595433d48a157ff0ecc2b9780ca9be20da1ca9a7a1f726f789e0e6e64", | |
| "reports/train_results.json": "4e41a2e53d7d7bf41840368658eda56425258ef1839adc1ff6f2d7345865d468" | |
| } | |