Instructions to use devkyle/Akan-tiny-2000ms-1k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use devkyle/Akan-tiny-2000ms-1k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="devkyle/Akan-tiny-2000ms-1k")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("devkyle/Akan-tiny-2000ms-1k") model = AutoModelForSpeechSeq2Seq.from_pretrained("devkyle/Akan-tiny-2000ms-1k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0b019d1eef821eda626be15c2803a4ab9136ded8c7821fef28e27841ee1f6b80
- Size of remote file:
- 5.43 kB
- SHA256:
- 02df131f4f177afaac4d4cfef1052f21ad180ceafbe87e8b4ce649f2af572ece
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