Instructions to use hf-tiny-model-private/tiny-random-MarkupLMForQuestionAnswering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-MarkupLMForQuestionAnswering with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="hf-tiny-model-private/tiny-random-MarkupLMForQuestionAnswering")# Load model directly from transformers import AutoProcessor, AutoModelForQuestionAnswering processor = AutoProcessor.from_pretrained("hf-tiny-model-private/tiny-random-MarkupLMForQuestionAnswering") model = AutoModelForQuestionAnswering.from_pretrained("hf-tiny-model-private/tiny-random-MarkupLMForQuestionAnswering") - Notebooks
- Google Colab
- Kaggle
File size: 101 Bytes
0391058 | 1 2 3 4 5 | {
"feature_extractor_type": "MarkupLMFeatureExtractor",
"processor_class": "MarkupLMProcessor"
}
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