Automatic Speech Recognition
Transformers
PyTorch
JAX
TensorBoard
ONNX
Safetensors
whisper
audio
asr
hf-asr-leaderboard
Instructions to use NbAiLabBeta/nb-whisper-medium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLabBeta/nb-whisper-medium with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NbAiLabBeta/nb-whisper-medium")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("NbAiLabBeta/nb-whisper-medium") model = AutoModelForSpeechSeq2Seq.from_pretrained("NbAiLabBeta/nb-whisper-medium") - Notebooks
- Google Colab
- Kaggle
Update model_def.json
Browse files- model_def.json +10 -0
model_def.json
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{
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"template_url": "https://raw.githubusercontent.com/NbAiLab/nb-whisper/main/template.md",
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"replacements": {
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"#Finetuned#": "",
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"#Size#": "Medium",
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"#size#": "medium",
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"#model_name#": "NbAiLabBeta/nb-whisper-medium"
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}
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}
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