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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2844c515d15d35ee26c89e0e3597cd492a8c5333ee18bd59212ce497c8a51c4b
- Size of remote file:
- 921 kB
- SHA256:
- a5edda2d43f5d1b0fe5af8c78cdc508773c4146dd5e1e7eff0d9bf7de05780ad
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