Instructions to use ying-tina/temp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ying-tina/temp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ying-tina/temp", device_map="auto")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("ying-tina/temp") model = AutoModelForCTC.from_pretrained("ying-tina/temp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
add tokenizer
Browse files- vocab.json +1 -1
vocab.json
CHANGED
|
@@ -1 +1 @@
|
|
| 1 |
-
{"
|
|
|
|
| 1 |
+
{"g": 1, "f": 2, "i": 3, "'": 4, "u": 5, "w": 6, "p": 7, "v": 8, "o": 9, "d": 10, "q": 11, "a": 12, "y": 13, "z": 14, "c": 15, "n": 16, "s": 17, "t": 18, "r": 19, "e": 20, "k": 21, "m": 22, "b": 23, "j": 24, "l": 25, "x": 26, "h": 27, "|": 0, "[UNK]": 28, "[PAD]": 29}
|