Instructions to use mazkooleg/0-9up-data2vec-audio-base-960h-ft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mazkooleg/0-9up-data2vec-audio-base-960h-ft with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="mazkooleg/0-9up-data2vec-audio-base-960h-ft")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForAudioClassification tokenizer = AutoTokenizer.from_pretrained("mazkooleg/0-9up-data2vec-audio-base-960h-ft") model = AutoModelForAudioClassification.from_pretrained("mazkooleg/0-9up-data2vec-audio-base-960h-ft", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 134 Bytes
9b0f341 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:2c4246ff930149ee1e87fcf23fabd6cd5b7f566c7a7d7ecd66b80b3e816a9746
size 373533805
|