Instructions to use enactic/avista-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use enactic/avista-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="enactic/avista-base", trust_remote_code=True)# Load model directly from transformers import AutoModelForSpeechSeq2Seq model = AutoModelForSpeechSeq2Seq.from_pretrained("enactic/avista-base", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- eed9eabe5a8cd510ba0e6d707a3e9233f40283efb2d628a32bb9fb6b39ee17ab
- Size of remote file:
- 653 MB
- SHA256:
- 35ee1a95844cd8f2f45822d0c8c5f167727337bc5a616e95a02b4b0a4341ca2b
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