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:
- b4bca107441aadcdf1271e328c9b37d52346b42912538aacac34d30639720a56
- Size of remote file:
- 33.7 MB
- SHA256:
- bbcdf4627ad7c57fc775d8114e15f083d4e1a2b34ee579f44f184bfc1bb473a2
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