Instructions to use hf-internal-testing/tiny-random-LukeForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-LukeForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-random-LukeForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-LukeForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-random-LukeForMaskedLM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f3e550d571b8d04a09b6a5e4a43bfcd2f22d7dc522359abe94fac3ca55c113f8
- Size of remote file:
- 7.02 MB
- SHA256:
- 6dcf958d2170ba38d3ff4baa10a6a539ea3756c734e74b18533842ea90de8948
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