Instructions to use sileod/deberta-v3-base-tasksource-paraphrase with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sileod/deberta-v3-base-tasksource-paraphrase with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sileod/deberta-v3-base-tasksource-paraphrase")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sileod/deberta-v3-base-tasksource-paraphrase") model = AutoModelForSequenceClassification.from_pretrained("sileod/deberta-v3-base-tasksource-paraphrase", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from sileod/deberta-v3-base-tasksource-paraphrase: direct link, hf CLI and curl.
- Browser
- Download file 738 MB
-
https://huggingface.co/sileod/deberta-v3-base-tasksource-paraphrase/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://sileod/deberta-v3-base-tasksource-paraphrase/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/sileod/deberta-v3-base-tasksource-paraphrase/resolve/main/pytorch_model.bin
738 MB
- Xet hash:
- 5762853807c599f77b425eda793004e40937ba63744507b76b40cb7511de61b9
- Size of remote file:
- 738 MB
- SHA256:
- c0c36baeaa404cb056ea1da737391dc0611f918d4af2a6c97a93f5c6d1353f82
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