Automatic Speech Recognition
Transformers
PyTorch
TensorFlow
JAX
TensorBoard
ONNX
Safetensors
whisper
audio
asr
hf-asr-leaderboard
Instructions to use NbAiLabBeta/nb-whisper-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLabBeta/nb-whisper-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="NbAiLabBeta/nb-whisper-tiny")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("NbAiLabBeta/nb-whisper-tiny") model = AutoModelForSpeechSeq2Seq.from_pretrained("NbAiLabBeta/nb-whisper-tiny") - Notebooks
- Google Colab
- Kaggle
Update config.json
Browse files- config.json +2 -2
config.json
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{
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"_name_or_path": "
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"activation_dropout": 0.1,
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"activation_function": "gelu",
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"apply_spec_augment": false,
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"torch_dtype": "float32",
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"transformers_version": "4.
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"use_cache": true,
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"use_weighted_layer_sum": false,
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"vocab_size": 51865
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{
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"_name_or_path": "./",
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"activation_dropout": 0.1,
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"activation_function": "gelu",
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"apply_spec_augment": false,
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],
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"torch_dtype": "float32",
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"transformers_version": "4.36.1",
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"use_cache": true,
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"use_weighted_layer_sum": false,
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"vocab_size": 51865
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