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:
- 5aca47f51917da330a6989f2a7e14d048a838a10f0ff7e18d94050e299845f85
- Size of remote file:
- 325 kB
- SHA256:
- e9587a9b47b403fa7da84b45f6a8141f6c1065420328153929b32517c1d57e57
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