Instructions to use ydshieh/tiny-random-DebertaV2ForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ydshieh/tiny-random-DebertaV2ForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ydshieh/tiny-random-DebertaV2ForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ydshieh/tiny-random-DebertaV2ForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("ydshieh/tiny-random-DebertaV2ForMaskedLM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c7ca405afe12d046e58e8071c374c8326ad86232dd85926b7ffb456f55746300
- Size of remote file:
- 376 kB
- SHA256:
- a62367125851137b13535e84787a23d5831004bec2da2606576524110800f267
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