Instructions to use Dmitriy/test555 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Dmitriy/test555 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Dmitriy/test555")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Dmitriy/test555") model = AutoModelForSpeechSeq2Seq.from_pretrained("Dmitriy/test555") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4d7e319342aff875f26965ace9b42c74308e19b84e270e97e179fb96e381bb1c
- Size of remote file:
- 151 MB
- SHA256:
- 98b36c14565ea9e70ce4e0ded783957e29232823bd3c49bfc0a19bff764b746e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.