Instructions to use AIArchiveInfo/deberta-v3-large-zeroshot-v2.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AIArchiveInfo/deberta-v3-large-zeroshot-v2.0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("zero-shot-classification", model="AIArchiveInfo/deberta-v3-large-zeroshot-v2.0")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("AIArchiveInfo/deberta-v3-large-zeroshot-v2.0") model = AutoModelForSequenceClassification.from_pretrained("AIArchiveInfo/deberta-v3-large-zeroshot-v2.0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download onnx/tokenizer.json from AIArchiveInfo/deberta-v3-large-zeroshot-v2.0: direct link, hf CLI and curl.
- Browser
- Download file 8.65 MB
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https://huggingface.co/AIArchiveInfo/deberta-v3-large-zeroshot-v2.0/resolve/main/onnx/tokenizer.json
- Command line
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hf download hf://AIArchiveInfo/deberta-v3-large-zeroshot-v2.0/onnx/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/AIArchiveInfo/deberta-v3-large-zeroshot-v2.0/resolve/main/onnx/tokenizer.json
8.65 MB
File too large to display, you can check the raw version instead.