Zero-Shot Classification
Transformers
Safetensors
German
deberta-v2
text-classification
Generated from Trainer
Instructions to use michaelp11/zeroshot-classification-de with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use michaelp11/zeroshot-classification-de with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="michaelp11/zeroshot-classification-de")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("michaelp11/zeroshot-classification-de") model = AutoModelForSequenceClassification.from_pretrained("michaelp11/zeroshot-classification-de", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from michaelp11/zeroshot-classification-de: direct link, hf CLI and curl.
- Browser
- Download file 4.92 kB
-
https://huggingface.co/michaelp11/zeroshot-classification-de/resolve/main/training_args.bin
- Command line
-
hf download hf://michaelp11/zeroshot-classification-de/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/michaelp11/zeroshot-classification-de/resolve/main/training_args.bin
4.92 kB
- Xet hash:
- f36229a575329d23e96467bfd27fb282853808e5003424bac7be38f18376396a
- Size of remote file:
- 4.92 kB
- SHA256:
- 77f5245fedf26e8b1f2616a484b99fc5ff3d0d991cb2b395101884edd807dc0a
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