Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Central Kurdish
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use PawanKrd/asr-large-ckb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PawanKrd/asr-large-ckb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="PawanKrd/asr-large-ckb", device_map="auto")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("PawanKrd/asr-large-ckb") model = AutoModelForSpeechSeq2Seq.from_pretrained("PawanKrd/asr-large-ckb", device_map="auto") - Notebooks
- Google Colab
- Kaggle
timestamps
#2
by ArasRahman - opened
Hi, thanks for training this β impressive WER (4.13%) for a low-resource
language like Sorani Kurdish!
Question: does this model support word-level or sentence-level timestamps
(forced alignment), either built-in or via a companion model? I'm using it
for a video dubbing pipeline where I need accurate start/end times for
each sentence, not just the transcribed text.
If it doesn't currently, do you know of a forced-alignment approach that
works well with this model's output (e.g., CTC-segmentation, a
wav2vec2-based aligner, or similar)?