Instructions to use halcyonzhou/1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use halcyonzhou/1.0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="halcyonzhou/1.0")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("halcyonzhou/1.0") model = AutoModelForCTC.from_pretrained("halcyonzhou/1.0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- df7b01699c58399131819bd6a0abb9c88dfa72a23352155550a52d8e9eae38ae
- Size of remote file:
- 5.3 kB
- SHA256:
- dc26f13e90f855378cb07503ea94bda175c5513979d50aee0b6e8b343bdde56c
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