Instructions to use Sjdan/torgo_ep50_bs8_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sjdan/torgo_ep50_bs8_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Sjdan/torgo_ep50_bs8_2")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Sjdan/torgo_ep50_bs8_2") model = AutoModelForCTC.from_pretrained("Sjdan/torgo_ep50_bs8_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download vocab.json from Sjdan/torgo_ep50_bs8_2: direct link, hf CLI and curl.
- Browser
- Download file 353 Bytes
-
https://huggingface.co/Sjdan/torgo_ep50_bs8_2/resolve/main/vocab.json
- Command line
-
hf download hf://Sjdan/torgo_ep50_bs8_2/vocab.json
-
curl -L -o vocab.json https://huggingface.co/Sjdan/torgo_ep50_bs8_2/resolve/main/vocab.json
353 Bytes
| { | |
| "'": 3, | |
| "1": 21, | |
| "3": 23, | |
| "[PAD]": 31, | |
| "[UNK]": 30, | |
| "a": 26, | |
| "b": 15, | |
| "c": 5, | |
| "d": 2, | |
| "e": 20, | |
| "f": 13, | |
| "g": 0, | |
| "h": 28, | |
| "i": 11, | |
| "j": 1, | |
| "k": 4, | |
| "l": 24, | |
| "m": 29, | |
| "n": 12, | |
| "o": 10, | |
| "p": 25, | |
| "q": 17, | |
| "r": 14, | |
| "s": 16, | |
| "t": 8, | |
| "u": 6, | |
| "v": 9, | |
| "w": 19, | |
| "x": 22, | |
| "y": 7, | |
| "z": 18, | |
| "|": 27 | |
| } | |