Instructions to use Raffay/local_speech_processing_project_wav2vec2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Raffay/local_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/local_speech_processing_project_wav2vec2")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Raffay/local_speech_processing_project_wav2vec2") model = AutoModelForCTC.from_pretrained("Raffay/local_speech_processing_project_wav2vec2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download vocab.json from Raffay/local_speech_processing_project_wav2vec2: direct link, hf CLI and curl.
- Browser
- Download file 445 Bytes
-
https://huggingface.co/Raffay/local_speech_processing_project_wav2vec2/resolve/main/vocab.json
- Command line
-
hf download hf://Raffay/local_speech_processing_project_wav2vec2/vocab.json
-
curl -L -o vocab.json https://huggingface.co/Raffay/local_speech_processing_project_wav2vec2/resolve/main/vocab.json
445 Bytes
| {"ف": 0, "ص": 1, "ٹ": 2, "ذ": 3, "ب": 4, "ڈ": 5, "ہ": 6, "آ": 7, "م": 8, "ئ": 9, "ے": 10, "ح": 11, "س": 12, "ر": 13, "ت": 14, "ظ": 15, "ھ": 16, " ": 17, "ع": 18, "د": 19, "ز": 20, "گ": 21, "ژ": 22, "ل": 23, "ا": 24, "ق": 25, "خ": 26, "غ": 27, "ط": 28, "و": 29, "ث": 30, "ء": 31, "ک": 32, "ں": 33, "ج": 34, "ش": 35, "ن": 36, "ڑ": 37, "چ": 38, "پ": 39, "ی": 40, "ض": 41, "ؤ": 42, "[UNK]": 43, "[PAD]": 44} |