Instructions to use BadreddineHug/LayoutLMv3_large_3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BadreddineHug/LayoutLMv3_large_3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="BadreddineHug/LayoutLMv3_large_3")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("BadreddineHug/LayoutLMv3_large_3") model = AutoModelForTokenClassification.from_pretrained("BadreddineHug/LayoutLMv3_large_3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bbcc52ebd38bb509ad1755b0971109b4b935608acfcb64ea7c2462fd660234fa
- Size of remote file:
- 3.96 kB
- SHA256:
- 7d86f090c7ef9e8176dba9c652f0361fbef1ab2802834883b5f3e5dae0051cc4
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