Instructions to use rohitp1/libri-alpha-1-Temp-1-processor-change with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rohitp1/libri-alpha-1-Temp-1-processor-change with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="rohitp1/libri-alpha-1-Temp-1-processor-change")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("rohitp1/libri-alpha-1-Temp-1-processor-change") model = AutoModelForCTC.from_pretrained("rohitp1/libri-alpha-1-Temp-1-processor-change") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 103addc8febc73c4420b16cc81c2a37b0856a95e232934cbbc05093f1061db03
- Size of remote file:
- 3.44 kB
- SHA256:
- 4c77cf81f5ce20cdf1c28f1c0a98ffa0cc9e04dbbd908e33c1cfe42663acf5a5
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.