Instructions to use hf-internal-testing/tiny-random-data2vec-seq-class with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-data2vec-seq-class with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="hf-internal-testing/tiny-random-data2vec-seq-class")# Load model directly from transformers import AutoTokenizer, AutoModelForAudioClassification tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-data2vec-seq-class") model = AutoModelForAudioClassification.from_pretrained("hf-internal-testing/tiny-random-data2vec-seq-class", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 260868fd29e414d40fa13e17784d0f526ae5c10c198001654f685714ccc1301a
- Size of remote file:
- 484 kB
- SHA256:
- 94cc07712cb2fabcfdb8052a6df11c5cd5f9efdcdc930f83f405cd1b30c055d8
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