Instructions to use basilkr/CHCK1_DICT_LUKE_40 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use basilkr/CHCK1_DICT_LUKE_40 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="basilkr/CHCK1_DICT_LUKE_40")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("basilkr/CHCK1_DICT_LUKE_40") model = AutoModelForSpeechSeq2Seq.from_pretrained("basilkr/CHCK1_DICT_LUKE_40", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c607eecd27911c9a09163c8c5672d66ce8b813f2b7150c4f2f37fbf26ed3d0f6
- Size of remote file:
- 6.17 GB
- SHA256:
- 89f745e58b8b9f50da2521334488b3773b9c7442fb57a3abe43fd23378368cb0
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