Instructions to use enactic/avista-base-plus with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use enactic/avista-base-plus with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="enactic/avista-base-plus", trust_remote_code=True)# Load model directly from transformers import AutoModelForSpeechSeq2Seq model = AutoModelForSpeechSeq2Seq.from_pretrained("enactic/avista-base-plus", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 965ebd43640335b08160b7604e9e373326d2fff072c350c0497f525f7d506ee2
- Size of remote file:
- 653 MB
- SHA256:
- 281a80d89aa32a8149efd9c1cc54a7e2cbf87749c7968594a1d7a08bbcb05a1d
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