Instructions to use cliang1453/deberta-v3-base-mrpc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cliang1453/deberta-v3-base-mrpc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="cliang1453/deberta-v3-base-mrpc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("cliang1453/deberta-v3-base-mrpc") model = AutoModelForSequenceClassification.from_pretrained("cliang1453/deberta-v3-base-mrpc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:fe5b32428acee88f70e2310ad31a6392d949a76a51a52dc7798fb7b4be35a5e1
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size 737723472
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