Instructions to use hf-internal-testing/tiny-random-LayoutLMModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-LayoutLMModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-LayoutLMModel")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hf-internal-testing/tiny-random-LayoutLMModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-LayoutLMModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a7390bdb075cf61ff52636c728f42078bc57b95fb7bd829e9229fe5def9202b2
- Size of remote file:
- 890 kB
- SHA256:
- dfd13c7ff46bb4a4d38936a4295dc94ec04d6ae9bd67780cb0e9854808045c75
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