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
Add Open ASR Leaderboard evaluation results
#2
by SaylorTwift HF Staff - opened
No description provided.
Thank you for this contribution! We're just about to upload an update to the model, which will change the performance results. We will close this PR with the older scores and make the adjustments to match the markdown changes you've proposed with the new performance results.
travisdewolf changed pull request status to closed