Instructions to use hf-internal-testing/tiny-layoutlm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-layoutlm with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="hf-internal-testing/tiny-layoutlm")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-layoutlm") model = AutoModelForMaskedLM.from_pretrained("hf-internal-testing/tiny-layoutlm") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7269b12c094211b7e9faec7b3eb27cba4909ca3fdad061bc808658960816f08e
- Size of remote file:
- 874 kB
- SHA256:
- 385846e7fe0ab3bdfe5f141c5f01354d67cb1015d2f3b14f7cd259dd289e93bf
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