Instructions to use kitjesen/MinerU with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kitjesen/MinerU with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="kitjesen/MinerU", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("kitjesen/MinerU", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1e55a2ad9efa10c6ae088fd9fc1bf82260f0059ddd048df57a97063cc140817c
- Size of remote file:
- 3.39 MB
- SHA256:
- 6bff0a7f8c27272ea2118d7dc7baa1afeb706ffae8b36dc3a13628a8a3682880
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