Instructions to use Borsa356/CATeniser_de_nli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Borsa356/CATeniser_de_nli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Borsa356/CATeniser_de_nli")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Borsa356/CATeniser_de_nli") model = AutoModelForSequenceClassification.from_pretrained("Borsa356/CATeniser_de_nli", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Borsa356/CATeniser_de_nli: direct link, hf CLI and curl.
- Browser
- Download file 729 kB
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https://huggingface.co/Borsa356/CATeniser_de_nli/resolve/main/tokenizer.json
- Command line
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hf download hf://Borsa356/CATeniser_de_nli/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/Borsa356/CATeniser_de_nli/resolve/main/tokenizer.json
729 kB
File too large to display, you can check the raw version instead.