Instructions to use Siyong/MT_RN_LM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Siyong/MT_RN_LM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Siyong/MT_RN_LM")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Siyong/MT_RN_LM") model = AutoModelForCTC.from_pretrained("Siyong/MT_RN_LM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download vocab.json from Siyong/MT_RN_LM: direct link, hf CLI and curl.
- Browser
- Download file 268 Bytes
-
https://huggingface.co/Siyong/MT_RN_LM/resolve/main/vocab.json
- Command line
-
hf download hf://Siyong/MT_RN_LM/vocab.json
-
curl -L -o vocab.json https://huggingface.co/Siyong/MT_RN_LM/resolve/main/vocab.json
268 Bytes
| {"k": 0, "n": 1, "f": 3, "g": 4, "d": 5, "o": 6, "l": 7, "h": 8, "b": 9, "e": 10, "p": 11, "u": 12, "m": 13, "v": 14, "a": 15, "y": 16, "r": 17, "q": 18, "s": 19, "x": 20, "z": 21, "i": 22, "c": 23, "j": 24, "'": 25, "w": 26, "t": 27, "[UNK]": 28, "[PAD]": 29, "|": 2} |