Audio Classification
Transformers
TensorBoard
Safetensors
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use JasHugF/whisper-tiny-tel-tam-try1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JasHugF/whisper-tiny-tel-tam-try1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="JasHugF/whisper-tiny-tel-tam-try1")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("JasHugF/whisper-tiny-tel-tam-try1") model = AutoModelForAudioClassification.from_pretrained("JasHugF/whisper-tiny-tel-tam-try1") - Notebooks
- Google Colab
- Kaggle
whisper-tiny-tel-tam
This model is a fine-tuned version of openai/whisper-tiny on the Speech Commands dataset.
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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Model tree for JasHugF/whisper-tiny-tel-tam-try1
Base model
openai/whisper-tinyEvaluation results
- Accuracy on Speech Commandsself-reported0.977