Instructions to use hf-internal-testing/tiny-random-LayoutLMv3Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-LayoutLMv3Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-LayoutLMv3Model")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-LayoutLMv3Model") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-LayoutLMv3Model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d57fe228182ff3fd273452b05c62a1fb4cae5dff05e8bccacf49e7d08e974d2f
- Size of remote file:
- 451 kB
- SHA256:
- eb34a02465e412c7f9433aeb7d25dd30f62f55f9db3beab9357577758bd754fc
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