Instructions to use speechdata/speech-or-sound with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use speechdata/speech-or-sound with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="speechdata/speech-or-sound")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("speechdata/speech-or-sound") model = AutoModelForAudioClassification.from_pretrained("speechdata/speech-or-sound", device_map="auto") - Notebooks
- Google Colab
- Kaggle
metadata
language:
- en
base_model:
- openai/whisper-tiny
pipeline_tag: audio-classification
library_name: transformers
datasets:
- speechdata/speech-or-sound
private for now, more details coming soon
very experimental model so please DM me on X for access https://x.com/realmrfakename