Instructions to use SCUT-DLVCLab/lilt-roberta-en-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SCUT-DLVCLab/lilt-roberta-en-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="SCUT-DLVCLab/lilt-roberta-en-base")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("SCUT-DLVCLab/lilt-roberta-en-base") model = AutoModel.from_pretrained("SCUT-DLVCLab/lilt-roberta-en-base") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e10173a823adedb7ced091dafc1593bb46ce677b6bf3f567dd7f6c95664c52b4
- Size of remote file:
- 523 MB
- SHA256:
- 086e5582fb92517fc047c169ea2c863de997f47a928e173afab36186db1f1242
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