Instructions to use aist-eart/toast with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aist-eart/toast with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("aist-eart/toast", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download processor_config.json from aist-eart/toast: direct link, hf CLI and curl.
- Browser
- Download file 1.06 kB
-
https://huggingface.co/aist-eart/toast/resolve/main/processor_config.json
- Command line
-
hf download hf://aist-eart/toast/processor_config.json
-
curl -L -o processor_config.json https://huggingface.co/aist-eart/toast/resolve/main/processor_config.json
1.06 kB
| { | |
| "auto_map": { | |
| "AutoProcessor": "toast.TOASTActionProcessor" | |
| }, | |
| "processor_class": "TOASTActionProcessor", | |
| "spm_model_file": "spm_toast_droid-eef.model", | |
| "quantization": "dct", | |
| "quantizer_kwargs": { | |
| "scale": 10, | |
| "min_token": -113, | |
| "num_symbols": 189 | |
| }, | |
| "vocab_size": 512, | |
| "order": "dimension", | |
| "alphabet": "!\"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\\]^_`abcdefghijklmnopqrstuvwxyz{|}~\u00a1\u00a2\u00a3\u00a4\u00a5\u00a6\u00a7\u00a9\u00ab\u00ac\u00ae\u00b0\u00b1\u00b6\u00b7\u00bb\u00bf\u00c0\u00c1\u00c2\u00c3\u00c4\u00c5\u00c6\u00c7\u00c8\u00c9\u00ca\u00cb\u00cc\u00cd\u00ce\u00cf\u00d0\u00d1\u00d2\u00d3\u00d4\u00d5\u00d6\u00d7\u00d8\u00d9\u00da\u00db\u00dc\u00dd\u00de\u00df\u00e0\u00e1\u00e2\u00e3\u00e4\u00e5\u00e6\u00e7\u00e8\u00e9\u00ea\u00eb\u00ec\u00ed\u00ee\u00ef\u00f0\u00f1\u00f2\u00f3\u00f4\u00f5\u00f6\u00f7\u00f8\u00f9\u00fa\u00fb\u00fc\u00fd\u00fe\u00ff\u0100\u0101\u0102\u0103\u0104\u0105\u0106\u0107\u0108\u0109\u010a\u010b\u010c\u010d", | |
| "action_dim": null, | |
| "time_horizon": null | |
| } | |