Audio Classification
Transformers
TensorBoard
Safetensors
audio-spectrogram-transformer
Generated from Trainer
Eval Results (legacy)
Instructions to use mahmoudmamdouh13/ast-mlcommons-speech-commands with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mahmoudmamdouh13/ast-mlcommons-speech-commands with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="mahmoudmamdouh13/ast-mlcommons-speech-commands")# Load model directly from transformers import AutoFeatureExtractor, AutoModelForAudioClassification extractor = AutoFeatureExtractor.from_pretrained("mahmoudmamdouh13/ast-mlcommons-speech-commands") model = AutoModelForAudioClassification.from_pretrained("mahmoudmamdouh13/ast-mlcommons-speech-commands", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
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# Audio Spectrogram Transformer (AST) Fine-Tuned on MLCommons Multilingual Spoken Words + Google Speech Commands
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## Model Details
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---
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library_name: transformers
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license: bsd-3-clause
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base_model: MIT/ast-finetuned-speech-commands-v2
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tags:
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- generated_from_trainer
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datasets:
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- audiofolder
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metrics:
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- precision
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- recall
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- f1
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model-index:
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- name: ast-finetuned-speech-commands-v2-finetuned-keyword-spotting-finetuned-keyword-spotting
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results:
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- task:
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name: Audio Classification
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type: audio-classification
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dataset:
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name: audiofolder
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type: audiofolder
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config: default
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split: validation
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args: default
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metrics:
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- name: Precision
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type: precision
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value: 0.9861935383961439
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- name: Recall
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type: recall
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value: 0.9861649413727126
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- name: F1
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type: f1
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value: 0.9861100898918743
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---
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# Audio Spectrogram Transformer (AST) Fine-Tuned on MLCommons Multilingual Spoken Words + Google Speech Commands
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## Model Details
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