Instructions to use AuroraAI-Research/AuroraASR-1M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AuroraAI-Research/AuroraASR-1M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="AuroraAI-Research/AuroraASR-1M", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCTC model = AutoModelForCTC.from_pretrained("AuroraAI-Research/AuroraASR-1M", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 390 Bytes
54e9f52 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | {
"auto_map": {
"AutoFeatureExtractor": "feature_extraction_auroraasr.AuroraASRFeatureExtractor"
},
"feature_extractor_type": "AuroraASRFeatureExtractor",
"feature_size": 80,
"fmax": 8000.0,
"fmin": 20.0,
"hop_length": 160,
"n_fft": 512,
"padding_side": "right",
"padding_value": 0.0,
"return_attention_mask": true,
"sampling_rate": 16000,
"win_length": 400
}
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