Instructions to use hf-internal-testing/tiny-random-MarkupLMModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MarkupLMModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-MarkupLMModel")# Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-MarkupLMModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-MarkupLMModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 415886cbfa5abc919b1003e1dacab4bd3990d99a1255b4683049f4f9c24285a6
- Size of remote file:
- 6.94 MB
- SHA256:
- c6c3a7a9bca9f19b233403bb8dccfe4c3816c2805eebb62b031bcfaf22a0e90c
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