Instructions to use hf-internal-testing/tiny-random-DebertaV2ForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-DebertaV2ForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-random-DebertaV2ForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-DebertaV2ForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-random-DebertaV2ForMaskedLM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cd21f9022ef4af3a6fc5bed5fc0dda46119771a193a07fd07c07b781bc2f2989
- Size of remote file:
- 17.1 MB
- SHA256:
- c8d173965cfbfb869b7392f6088a5666acb6e0cb60c59c06db01cd70d691f067
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