Instructions to use enactic/avista-large-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use enactic/avista-large-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="enactic/avista-large-v2", trust_remote_code=True)# Load model directly from transformers import AutoModelForSpeechSeq2Seq model = AutoModelForSpeechSeq2Seq.from_pretrained("enactic/avista-large-v2", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6f0b40e742961337ebfeed1ce979af28a4931f1a991476d6ee0026b3bee3305d
- Size of remote file:
- 1.92 GB
- SHA256:
- 3a074e858305aa8fb2bb8f5ca5a860943c4ef14aa75f7e1cc6a2972335f691fc
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