Instructions to use shangrilar/cross-encoder-klue-mrc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shangrilar/cross-encoder-klue-mrc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="shangrilar/cross-encoder-klue-mrc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("shangrilar/cross-encoder-klue-mrc") model = AutoModelForSequenceClassification.from_pretrained("shangrilar/cross-encoder-klue-mrc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a7161f3c639edf1e3830503dee1b6e1278efdf2514c41a9d6287cde5aca34bf1
- Size of remote file:
- 442 MB
- SHA256:
- e7ef8748728a18725eab356261174f1217b5f73ea0643989cb1103b31fa5a5d9
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