Instructions to use sweetcocoa/pop2piano with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sweetcocoa/pop2piano with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="sweetcocoa/pop2piano")# Load model directly from transformers import AutoModelForSpeechSeq2Seq model = AutoModelForSpeechSeq2Seq.from_pretrained("sweetcocoa/pop2piano", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4fbe761a73b07ca5c791f7a79fbe13a1eea350bdee3322336c47f5cc62972f81
- Size of remote file:
- 236 MB
- SHA256:
- 4ebff90f182961d1dc7c8cf481289b5c926610fe89993b5b02f1a61fb29dfa45
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.