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
File size: 460 Bytes
0e80266 32d6019 0e80266 32d6019 | 1 2 3 4 5 6 7 8 | # Upstream credits
Chaka-ASR is fine-tuned from badrex/Ethio-ASR-amharic, which declares CC BY 4.0, and builds on facebook/w2v-bert-2.0.
Adaptation used [Leyu Amharic speech datasets](https://huggingface.co/leyu-amharic) with WAXAL replay. Consult upstream model cards and dataset terms for attribution and applicable conditions.
Chaka-ASR is released under CC BY 4.0. See LICENSE for the license reference. This notice records upstream attribution.
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