Automatic Speech Recognition
Transformers
English
niagara-19m-batch
asr
speech
state-space-model
ssm
edge-ai
audio
on-device
real-time
low-power
low-latency
cpu
embedded
custom_code
Eval Results
Instructions to use abr-ai/niagara-19m-batch.en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use abr-ai/niagara-19m-batch.en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="abr-ai/niagara-19m-batch.en", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("abr-ai/niagara-19m-batch.en", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "feature_extractor_type": "FeatureExtractor", | |
| "processor_class": "FeatureExtractor", | |
| "auto_map": { | |
| "AutoFeatureExtractor": "feature_extraction.FeatureExtractor" | |
| }, | |
| "window_size_ms": 25, | |
| "window_stride_ms": 10, | |
| "mel_lower_edge_hertz": 0, | |
| "mel_upper_edge_hertz": 8000, | |
| "mel_num_bins": 80, | |
| "sample_rate": 16000, | |
| "padding_value": 1000.0 | |
| } | |