Instructions to use approach0/dpr-cotbert-320 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use approach0/dpr-cotbert-320 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="approach0/dpr-cotbert-320")# Load model directly from transformers import AutoTokenizer, DprEncoder tokenizer = AutoTokenizer.from_pretrained("approach0/dpr-cotbert-320") model = DprEncoder.from_pretrained("approach0/dpr-cotbert-320") - Notebooks
- Google Colab
- Kaggle
one interesting question...
Browse files
README.md
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example_title: "mathy"
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- text: "Proof by [MASK] that $n$ [MASK] $gt$ $3$ $n$ [MASK] $n$ [MASK] $6$"
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example_title: "mathy"
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license: mit
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---
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example_title: "mathy"
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- text: "Proof by [MASK] that $n$ [MASK] $gt$ $3$ $n$ [MASK] $n$ [MASK] $6$"
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example_title: "mathy"
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- text: "The goal of life is [MASK]."
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example_title: "philosophical"
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license: mit
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