Instructions to use jasper-lu/temp_markup with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jasper-lu/temp_markup with Transformers:
# Load model directly from transformers import AutoProcessor, MarkupLMForPretraining processor = AutoProcessor.from_pretrained("jasper-lu/temp_markup") model = MarkupLMForPretraining.from_pretrained("jasper-lu/temp_markup", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 211 Bytes
2cf97f7 | 1 2 3 4 5 6 7 8 9 | from handler import EndpointHandler
my_handler = EndpointHandler(path=".")
html_string = "<html> <head> <title>Page Title</title> </head> </html>"
payload = {"inputs": html_string}
print(my_handler(payload))
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