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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ddf88d72941eb119c9d9bc40bf8689950ff3f71e15ea6c4738d12eb519639f77
- Size of remote file:
- 12.3 GB
- SHA256:
- bd61703b198ccb01e4869537ea30f13bdd230bde88c378876d528e2aa74a4f52
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