Instructions to use roseman/whisper-medium-ckb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use roseman/whisper-medium-ckb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="roseman/whisper-medium-ckb")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("roseman/whisper-medium-ckb") model = AutoModelForSpeechSeq2Seq.from_pretrained("roseman/whisper-medium-ckb", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8ff184749c5de1d5fcd9117c17a79d45a3a57c5c6df52d3e88ce1eaba8b71dca
- Size of remote file:
- 3.06 GB
- SHA256:
- 0fcdc7a8bef67434d04f21e57ce0e301c7ec16140b6889bef2a9696bbe7d0fde
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.