Instructions to use enactic/avista-base-plus-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use enactic/avista-base-plus-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="enactic/avista-base-plus-v2", trust_remote_code=True)# Load model directly from transformers import AutoModelForSpeechSeq2Seq model = AutoModelForSpeechSeq2Seq.from_pretrained("enactic/avista-base-plus-v2", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 18f0ace2488982f77f093b711bd92c2f0eaa4fdd8b385d3eb9e5e32a0f5ee00b
- Size of remote file:
- 653 MB
- SHA256:
- 980ad84c1e5c8c4153ece7802e6ce6a8c4b0a0111f7c89ea05cd521af64cef57
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