Instructions to use devkyle/Akan-3-small-2000ms with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use devkyle/Akan-3-small-2000ms with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="devkyle/Akan-3-small-2000ms")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("devkyle/Akan-3-small-2000ms") model = AutoModelForSpeechSeq2Seq.from_pretrained("devkyle/Akan-3-small-2000ms", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5a86b3c3db4a332a3fcad30c08422108bbef73f943e9442e705e099307fdc561
- Size of remote file:
- 967 MB
- SHA256:
- bf444bd3b6ded3da8100b39a229ac1615f862b39149ac1695e6fd886eaaf02ab
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