Audio Classification
Transformers
TensorBoard
Safetensors
English
Bengali
wav2vec2
Generated from Trainer
Eval Results (legacy)
Instructions to use shhossain/wav2vec2-tiny-random-rodela-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shhossain/wav2vec2-tiny-random-rodela-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="shhossain/wav2vec2-tiny-random-rodela-classifier")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("shhossain/wav2vec2-tiny-random-rodela-classifier") model = AutoModelForAudioClassification.from_pretrained("shhossain/wav2vec2-tiny-random-rodela-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "do_normalize": true, | |
| "feature_extractor_type": "Wav2Vec2FeatureExtractor", | |
| "feature_size": 1, | |
| "padding_side": "right", | |
| "padding_value": 0.0, | |
| "processor_class": "Wav2Vec2Processor", | |
| "return_attention_mask": false, | |
| "sampling_rate": 16000 | |
| } | |