Instructions to use BadreddineHug/LayoutLMv3_batch_8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use BadreddineHug/LayoutLMv3_batch_8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="BadreddineHug/LayoutLMv3_batch_8")# Load model directly from transformers import AutoProcessor, AutoModelForTokenClassification processor = AutoProcessor.from_pretrained("BadreddineHug/LayoutLMv3_batch_8") model = AutoModelForTokenClassification.from_pretrained("BadreddineHug/LayoutLMv3_batch_8") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8afd43b6f6365d6b2bb731d569dd0763c4bc1ddb0b9f63ff0b76db32eea43b88
- Size of remote file:
- 3.96 kB
- SHA256:
- 8fa01ca6c3fd81e3431e0e8855a17191b67f403ff1ccf3534667a481979ef063
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