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 export_models.sh
Browse files- export_models.sh +2 -2
export_models.sh
CHANGED
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@@ -16,7 +16,7 @@ model.save_pretrained("./")
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print("Done.")
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print("Saving model to TensorFlow...", end=" ")
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tf_model = TFWhisperForConditionalGeneration.from_pretrained("./"
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tf_model.save_pretrained("./")
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print("Done.")
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@@ -41,7 +41,7 @@ print("Done")
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END
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echo "Saving model to GGML (whisper.cpp)..."
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wget -O convert-h5-to-ggml.py "https://raw.githubusercontent.com/
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mkdir -p whisper/assets
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wget -O whisper/assets/mel_filters.npz "https://github.com/openai/whisper/raw/c5d42560760a05584c1c79546a098287e5a771eb/whisper/assets/mel_filters.npz"
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python ./convert-h5-to-ggml.py ./ ./ ./
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print("Done.")
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print("Saving model to TensorFlow...", end=" ")
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+
tf_model = TFWhisperForConditionalGeneration.from_pretrained("./")
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tf_model.save_pretrained("./")
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print("Done.")
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END
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echo "Saving model to GGML (whisper.cpp)..."
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+
wget -O convert-h5-to-ggml.py "https://raw.githubusercontent.com/NbAiLab/nb-whisper/main/convert-h5-to-ggml.py"
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mkdir -p whisper/assets
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wget -O whisper/assets/mel_filters.npz "https://github.com/openai/whisper/raw/c5d42560760a05584c1c79546a098287e5a771eb/whisper/assets/mel_filters.npz"
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python ./convert-h5-to-ggml.py ./ ./ ./
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