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, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-MarkupLMModel") model = AutoModelForMultimodalLM.from_pretrained("hf-internal-testing/tiny-random-MarkupLMModel") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4d646d981c3f64fe67e9c6f64c4648c42b44f3e617916fcb2972bd4671b9d2c3
- Size of remote file:
- 6.97 MB
- SHA256:
- 159cb793fe3e6712d0f58f866e4c70f04e985ce4a244ed33f929d02a8e17bfa6
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