Instructions to use basilkr/MAL_DICT_CHECK4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use basilkr/MAL_DICT_CHECK4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="basilkr/MAL_DICT_CHECK4")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("basilkr/MAL_DICT_CHECK4") model = AutoModelForSpeechSeq2Seq.from_pretrained("basilkr/MAL_DICT_CHECK4") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 214612811ba59998d9cc093018732bd43601304aca1f30c3ebfc19487cd23994
- Size of remote file:
- 3.77 kB
- SHA256:
- 464fbe9d6245740c72abe77459bf2e94835a71d7ba01ab3b8dd59b2c73379f76
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