Instructions to use hts98/temp2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hts98/temp2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="hts98/temp2")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("hts98/temp2") model = AutoModelForSpeechSeq2Seq.from_pretrained("hts98/temp2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c5f0e63be19abc945d9e878a54d7dd23459f0bac457a885951a562785371573c
- Size of remote file:
- 3.71 kB
- SHA256:
- dea377d49770f46ef9f1e988a1b371a52cf6f6badede47fe51a8a8fe3ffd06a0
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