Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Safetensors
Urdu
wav2vec2
hf-asr-leaderboard
robust-speech-event
Eval Results (legacy)
Instructions to use kingabzpro/wav2vec2-60-urdu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kingabzpro/wav2vec2-60-urdu with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="kingabzpro/wav2vec2-60-urdu")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("kingabzpro/wav2vec2-60-urdu") model = AutoModelForCTC.from_pretrained("kingabzpro/wav2vec2-60-urdu", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download special_tokens_map.json from kingabzpro/wav2vec2-60-urdu: direct link, hf CLI and curl.
- Browser
- Download file 309 Bytes
-
https://huggingface.co/kingabzpro/wav2vec2-60-urdu/resolve/e6f5514cd75558e2c04cda888d96b1ef9984d4ed/special_tokens_map.json
- Command line
-
hf download hf://kingabzpro/wav2vec2-60-urdu@e6f5514cd75558e2c04cda888d96b1ef9984d4ed/special_tokens_map.json
-
curl -L -o special_tokens_map.json https://huggingface.co/kingabzpro/wav2vec2-60-urdu/resolve/e6f5514cd75558e2c04cda888d96b1ef9984d4ed/special_tokens_map.json
309 Bytes
| {"bos_token": "<s>", "eos_token": "</s>", "unk_token": "[UNK]", "pad_token": "[PAD]", "additional_special_tokens": [{"content": "<s>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}, {"content": "</s>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true}]} |