Automatic Speech Recognition
Transformers
PyTorch
Safetensors
Central Kurdish
wav2vec2
mozilla-foundation/common_voice_8_0
Generated from Trainer
robust-speech-event
model_for_talk
hf-asr-leaderboard
Eval Results (legacy)
Instructions to use Akashpb13/Central_kurdish_xlsr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Akashpb13/Central_kurdish_xlsr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Akashpb13/Central_kurdish_xlsr")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Akashpb13/Central_kurdish_xlsr") model = AutoModelForCTC.from_pretrained("Akashpb13/Central_kurdish_xlsr") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c67aeee9afb899718aa96094a1eca4b530ae6c1f8ff1c7fd2356e5305b923f97
- Size of remote file:
- 1.26 GB
- SHA256:
- 389a8c7465980807312bc135a917d9a93683a889e8be2b3158dd3c4f743d73fd
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