Instructions to use Raffay/speech_processing_project_wav2vec2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Raffay/speech_processing_project_wav2vec2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Raffay/speech_processing_project_wav2vec2")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Raffay/speech_processing_project_wav2vec2") model = AutoModelForCTC.from_pretrained("Raffay/speech_processing_project_wav2vec2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
add tokenizer
Browse files- vocab.json +1 -1
vocab.json
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{"ت": 0, "ذ": 1, "ق": 2, "ف": 3, "ئ": 4, "ٹ": 5, "ظ": 6, "ڈ": 7, "ک":
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{"ت": 0, "ذ": 1, "ق": 2, "ف": 3, "ئ": 4, "ٹ": 5, "ظ": 6, "ڈ": 7, "ک": 8, "ج": 9, "ا": 10, "ص": 11, "ھ": 12, "ہ": 13, "م": 14, "ر": 15, "ح": 16, "چ": 17, "ی": 18, "ء": 19, "گ": 20, "ے": 21, "آ": 22, "و": 23, "ڑ": 24, "ں": 25, "ض": 26, "پ": 27, "ل": 28, " ": 29, "ب": 30, "خ": 31, "س": 32, "ن": 33, "ؤ": 34, "ث": 35, "ط": 36, "ژ": 37, "غ": 38, "ش": 39, "ز": 40, "د": 41, "ع": 42, "[UNK]": 43, "[PAD]": 44}
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