Instructions to use Sahajtomar/German_Zeroshot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sahajtomar/German_Zeroshot with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="Sahajtomar/German_Zeroshot")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sahajtomar/German_Zeroshot") model = AutoModelForSequenceClassification.from_pretrained("Sahajtomar/German_Zeroshot", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Sahajtomar/German_Zeroshot: direct link, hf CLI and curl.
- Browser
- Download file 1.34 GB
-
https://huggingface.co/Sahajtomar/German_Zeroshot/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Sahajtomar/German_Zeroshot/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Sahajtomar/German_Zeroshot/resolve/main/pytorch_model.bin
1.34 GB
- Xet hash:
- 6da2d656f564d11d45fa3ecb8fb1de154a63944db33b9a967f5f03c798bc95d6
- Size of remote file:
- 1.34 GB
- SHA256:
- 23b452b9c617a509e68de66125b10c127d2a7369cbae22efcb52af3c9daebe68
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