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
Download requirements-example.txt from caesar-abrham/Chaka-ASR: direct link, hf CLI and curl.
- Browser
- Download file 177 Bytes
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https://huggingface.co/caesar-abrham/Chaka-ASR/resolve/main/requirements-example.txt
- Command line
-
hf download hf://caesar-abrham/Chaka-ASR/requirements-example.txt
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curl -L -o requirements-example.txt https://huggingface.co/caesar-abrham/Chaka-ASR/resolve/main/requirements-example.txt
177 Bytes
| # Example dependencies; install a hardware-compatible PyTorch build for CUDA. | |
| transformers>=5.16.1,<6 | |
| torch>=2.6 | |
| safetensors>=0.4 | |
| numpy>=1.26 | |
| scipy>=1.11 | |
| soundfile>=0.12 | |