Instructions to use devkyle/Akan-3-3000ms with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use devkyle/Akan-3-3000ms with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="devkyle/Akan-3-3000ms")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("devkyle/Akan-3-3000ms") model = AutoModelForSpeechSeq2Seq.from_pretrained("devkyle/Akan-3-3000ms", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 57714d9c9978363c5662f7939aabd9dcd0fb73a4fc1cd4b6fc5d2454493f42a0
- Size of remote file:
- 5.37 kB
- SHA256:
- 688d91b2d40847b241f97568b9dd86d870864c124075570d2660764ce2044ccc
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