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, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6a9fe78a7273da0d4c5e2ab73f3b595f57559dc857c1f235c99098a2b0da9210
- Size of remote file:
- 262 MB
- SHA256:
- 235087b163e5988299f0a1a3eccd55e7a0998ccffa15315571f727ca94dfe76f
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