Instructions to use L-NLProc/PredEx_XLNet_Large_Pred with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use L-NLProc/PredEx_XLNet_Large_Pred with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="L-NLProc/PredEx_XLNet_Large_Pred")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("L-NLProc/PredEx_XLNet_Large_Pred") model = AutoModel.from_pretrained("L-NLProc/PredEx_XLNet_Large_Pred", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from L-NLProc/PredEx_XLNet_Large_Pred: direct link, hf CLI and curl.
- Browser
- Download file 31 Bytes
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https://huggingface.co/L-NLProc/PredEx_XLNet_Large_Pred/resolve/main/README.md
- Command line
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hf download hf://L-NLProc/PredEx_XLNet_Large_Pred/README.md
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curl -L -o README.md https://huggingface.co/L-NLProc/PredEx_XLNet_Large_Pred/resolve/main/README.md
31 Bytes
metadata
license: apache-2.0