Instructions to use SlothBot/AN_demo_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SlothBot/AN_demo_v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="SlothBot/AN_demo_v2")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("SlothBot/AN_demo_v2") model = AutoModelForSpeechSeq2Seq.from_pretrained("SlothBot/AN_demo_v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d9820d0950559aedfe1f1f40606fcbbfe3a1e757f0b199335160439e72e78d2f
- Size of remote file:
- 967 MB
- SHA256:
- dd7afacfb011a717ba8ca9b98ff0afaca880b03a53a2b19db4920c7d11c93c13
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