Automatic Speech Recognition
Transformers
Safetensors
Amharic
wav2vec2-bert
amharic
speech-recognition
ctc
leyu
Instructions to use caesar-abrham/Chaka-ASR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use caesar-abrham/Chaka-ASR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="caesar-abrham/Chaka-ASR")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("caesar-abrham/Chaka-ASR") model = AutoModelForCTC.from_pretrained("caesar-abrham/Chaka-ASR", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Add Chaka-ASR model card, inference example, and upstream credits
Browse files
README.md
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## Evaluation
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| Leyu | 20.48 | 6.02 |
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## Evaluation
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| Dataset | WER (%) | CER (%) |
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| Leyu | 20.48 | 6.02 |
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