Instructions to use manuth/w6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use manuth/w6 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="manuth/w6")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("manuth/w6") model = AutoModelForSpeechSeq2Seq.from_pretrained("manuth/w6") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b54841ce3752ff978bb7a6ec088bdda4d7fd909eb1859f7b0cb56c75311f3ce3
- Size of remote file:
- 5.62 kB
- SHA256:
- 752c4b9dd4b0327487557971951ab86b490eb473712ea80c580e6c037000b8dd
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