Audio Classification
Transformers
ONNX
Safetensors
Transformers.js
English
wav2vec2
audio
keyword-spotting
speech-commands
Eval Results (legacy)
Instructions to use diegomponte/wav2vec2-base-speech-commands-35 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use diegomponte/wav2vec2-base-speech-commands-35 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="diegomponte/wav2vec2-base-speech-commands-35")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("diegomponte/wav2vec2-base-speech-commands-35") model = AutoModelForAudioClassification.from_pretrained("diegomponte/wav2vec2-base-speech-commands-35", device_map="auto") - Transformers.js
How to use diegomponte/wav2vec2-base-speech-commands-35 with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('audio-classification', 'diegomponte/wav2vec2-base-speech-commands-35'); - Notebooks
- Google Colab
- Kaggle
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