Instructions to use koreankiwi99/cross_encoder_distil_deberta_new_dev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use koreankiwi99/cross_encoder_distil_deberta_new_dev with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="koreankiwi99/cross_encoder_distil_deberta_new_dev")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("koreankiwi99/cross_encoder_distil_deberta_new_dev") model = AutoModelForSequenceClassification.from_pretrained("koreankiwi99/cross_encoder_distil_deberta_new_dev", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from koreankiwi99/cross_encoder_distil_deberta_new_dev: direct link, hf CLI and curl.
- Browser
- Download file 8.66 MB
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https://huggingface.co/koreankiwi99/cross_encoder_distil_deberta_new_dev/resolve/main/tokenizer.json
- Command line
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hf download hf://koreankiwi99/cross_encoder_distil_deberta_new_dev/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/koreankiwi99/cross_encoder_distil_deberta_new_dev/resolve/main/tokenizer.json
8.66 MB
File too large to display, you can check the raw version instead.