Instructions to use aksds/checkpoint-600 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aksds/checkpoint-600 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="aksds/checkpoint-600")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("aksds/checkpoint-600") model = AutoModelForSpeechSeq2Seq.from_pretrained("aksds/checkpoint-600", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 43c5e7cf311b41a8362f9c9e912fd860de3baeb774452a2e722d251a27495be5
- Size of remote file:
- 298 MB
- SHA256:
- f71fcced5aaa0eec0392b2f181697add067dc4d49fcf2e5b599e9ad92de40090
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