Instructions to use hadiqa123/train_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hadiqa123/train_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="hadiqa123/train_model")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("hadiqa123/train_model") model = AutoModelForCTC.from_pretrained("hadiqa123/train_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
add tokenizer
Browse files- vocab.json +1 -1
vocab.json
CHANGED
|
@@ -1 +1 @@
|
|
| 1 |
-
{"
|
|
|
|
| 1 |
+
{"d": 1, "x": 2, "s": 3, "l": 4, "f": 5, "e": 6, "o": 7, "p": 8, "u": 9, "k": 10, "r": 11, "j": 12, "'": 13, "t": 14, "q": 15, "w": 16, "y": 17, "b": 18, "v": 19, "z": 20, "m": 21, "i": 22, "a": 23, "n": 24, "$": 25, "g": 26, "c": 27, "h": 28, "|": 0, "[UNK]": 29, "[PAD]": 30}
|