Instructions to use hf-internal-testing/tiny-random-DebertaForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-DebertaForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-random-DebertaForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-DebertaForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-random-DebertaForMaskedLM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9308cd6d2277e92732daa1d7e97976a2c9c008da1f054f944be46a2b22690956
- Size of remote file:
- 355 kB
- SHA256:
- 9113227b2124f7456b286f86a616a987614c4ae47c7ef69a19120da809be2047
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