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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 93006a0776dbc55c4d0ab0a5deec768740e3abcea0ec2a6f13a9e6cff04dc4bc
- Size of remote file:
- 538 MB
- SHA256:
- 04836f5d563a2fe802cdb87556b105d61547e1f7a2767b10fa8b375576d3c88e
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