Instructions to use Dev372/output_model_dir with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Dev372/output_model_dir with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Dev372/output_model_dir")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Dev372/output_model_dir") model = AutoModelForSpeechSeq2Seq.from_pretrained("Dev372/output_model_dir", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 129 Bytes
ac924e0 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:e1cbcedc23c17dbf21f2eb06deba49bc9c996dcee8a04d2df543839e7f327759
size 5240
|