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:
- e37726a29d6ff19122c52037d62bae6760275993d5b88e9490663d45e0b6a388
- Size of remote file:
- 371 kB
- SHA256:
- b3390403fe832d2860c200212cb2e669aa1b67f53d3855aa7a0c69c0dff63e13
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