Instructions to use SCUT-DLVCLab/lilt-infoxlm-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SCUT-DLVCLab/lilt-infoxlm-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="SCUT-DLVCLab/lilt-infoxlm-base")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("SCUT-DLVCLab/lilt-infoxlm-base") model = AutoModel.from_pretrained("SCUT-DLVCLab/lilt-infoxlm-base") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 78ca3627103ddfec9e016143310a19a1371497b0893f0546fbdd20316d566007
- Size of remote file:
- 1.14 GB
- SHA256:
- b99bb35c2bf61b1352c43caa10281d011123e1ee77e0ec9c1d8edf96be1dae74
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