Instructions to use erayyapagci/balbal-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- NeMo
How to use erayyapagci/balbal-v1 with NeMo:
import nemo.collections.asr as nemo_asr asr_model = nemo_asr.models.ASRModel.from_pretrained("erayyapagci/balbal-v1") transcriptions = asr_model.transcribe(["file.wav"]) - Notebooks
- Google Colab
- Kaggle
Rename MihuAI turkish-stt-66m-v2 -> turkish-stt-v2; drop omniASR CTC 300M from the accuracy chart
d6adae7 verified Download assets/cpu-speed-vs-wer.webp from erayyapagci/balbal-v1: direct link, hf CLI and curl.
- Browser
- Download file 134 kB
-
https://huggingface.co/erayyapagci/balbal-v1/resolve/main/assets/cpu-speed-vs-wer.webp
- Command line
-
hf download hf://erayyapagci/balbal-v1/assets/cpu-speed-vs-wer.webp
-
curl -L -o cpu-speed-vs-wer.webp https://huggingface.co/erayyapagci/balbal-v1/resolve/main/assets/cpu-speed-vs-wer.webp
134 kB

- Xet hash:
- 2cc56cbd05b70866a7801460bc5c5e1d88b44f71cc98a6736b3c10bde94aa539
- Size of remote file:
- 134 kB
- SHA256:
- 4bc2e65b863c1296d02bdc7d860b32745f4922dd386904b03dd4cc095ecb0b88
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