Automatic Speech Recognition
Transformers
PyTorch
TensorFlow
JAX
ONNX
Safetensors
Lule Sami
whisper
audio
asr
hf-asr-leaderboard
Instructions to use NbAiLab/salmon-whisper-large-smj-lr7e-5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLab/salmon-whisper-large-smj-lr7e-5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NbAiLab/salmon-whisper-large-smj-lr7e-5")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("NbAiLab/salmon-whisper-large-smj-lr7e-5") model = AutoModelForSpeechSeq2Seq.from_pretrained("NbAiLab/salmon-whisper-large-smj-lr7e-5") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9513d98600291a09d083a070b08701604abfa9b4c1b5cd9e0912083a28cede8b
- Size of remote file:
- 3.09 GB
- SHA256:
- 4904544548000d1c853f89e55fa7a604d86f0609e4af311e2a805ef803cb854d
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