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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 020113e75bff72e0491b162daf9959d47ca9abe8cbf716ee3e9859fecae01e25
- Size of remote file:
- 661 kB
- SHA256:
- 3cbeeb2bc5d84151c2763d205f0df66ab114caa0f6e2e4af880d0349b3c0157c
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