Instructions to use hf-internal-testing/tiny-random-LayoutLMForMaskedLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-LayoutLMForMaskedLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-random-LayoutLMForMaskedLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-LayoutLMForMaskedLM") model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-random-LayoutLMForMaskedLM") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3cb861f4249f8d1dc1c824b77d302c69525a130b1ed39776db9c3102901585b5
- Size of remote file:
- 900 kB
- SHA256:
- 0450cde18a413d4d04b5b89a401a976ae0a4e22854e3d98ca548613f47a7cc72
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