Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
English
whisper
hf-asr-leaderboard
Generated from Trainer
Instructions to use lw2333/Hinghwa_ASR_ipa_local with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lw2333/Hinghwa_ASR_ipa_local with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="lw2333/Hinghwa_ASR_ipa_local")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("lw2333/Hinghwa_ASR_ipa_local") model = AutoModelForSpeechSeq2Seq.from_pretrained("lw2333/Hinghwa_ASR_ipa_local") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0072881063ad3462eedad8a87490228f177d7bc5a64388c9f6e7b3ae3a5b6666
- Size of remote file:
- 4.84 kB
- SHA256:
- bf24a9d6d9617b17760daf066e322ad41a4be4c7e4793c2ba6f82c974510023f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.