Automatic Speech Recognition
Transformers
PyTorch
Safetensors
Urdu
wav2vec2
mozilla-foundation/common_voice_7_0
Generated from Trainer
sv
robust-speech-event
model_for_talk
hf-asr-leaderboard
Instructions to use Maniac/wav2vec2-xls-r-urdu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Maniac/wav2vec2-xls-r-urdu with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Maniac/wav2vec2-xls-r-urdu")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Maniac/wav2vec2-xls-r-urdu") model = AutoModelForCTC.from_pretrained("Maniac/wav2vec2-xls-r-urdu", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| {"unk_token": "[UNK]", "bos_token": "<s>", "eos_token": "</s>", "pad_token": "[PAD]", "do_lower_case": false, "word_delimiter_token": "|", "special_tokens_map_file": null, "tokenizer_file": null, "name_or_path": "./", "tokenizer_class": "Wav2Vec2CTCTokenizer"} |