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")# pip install -U transformers accelerate # 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", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Commit History
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Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (02d8e60dfed14252e748d5d66a6b015c2b617015) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>96328fa
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Create README.md
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Upload tokenizer
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Remove name_or_path
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Upload model
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initial commit
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