Instructions to use hf-internal-testing/tiny-random-deberta-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-deberta-v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-deberta-v2")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-deberta-v2") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-deberta-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 66f575e4ffd8b087c683e6c31321463a7a839fefcc06d50fedcdf8c83eeccd1e
- Size of remote file:
- 50.1 MB
- SHA256:
- a06cb2d39733ccf7822b83f6d0573f8e6136a88cc7c31f071de810ffd16b611e
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