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:
- 96094db4302c8b12d7974a1816254b15b3e71fbe29f929769f16674e7d7d4f49
- Size of remote file:
- 4.66 kB
- SHA256:
- c1722e151c8d33544b7116258c326933418f6d9d8d3163643f071391c19b4d85
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