Instructions to use microsoft/DialogRPT-human-vs-rand with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/DialogRPT-human-vs-rand with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="microsoft/DialogRPT-human-vs-rand")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("microsoft/DialogRPT-human-vs-rand") model = AutoModelForSequenceClassification.from_pretrained("microsoft/DialogRPT-human-vs-rand") - Notebooks
- Google Colab
- Kaggle
Update README.md
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README.md
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| Context | Response | `human_vs_rand` score |
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| :------ | :------- | :------------: |
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| I love NLP! |
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| I love NLP! |
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### Contact:
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Please create an issue on [our repo](https://github.com/golsun/DialogRPT)
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| Context | Response | `human_vs_rand` score |
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| I love NLP! | He is a great basketball player. | 0.027 |
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| I love NLP! | Can you tell me how it works? | 0.754 |
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| I love NLP! | Me too! | 0.631 |
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### Contact:
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Please create an issue on [our repo](https://github.com/golsun/DialogRPT)
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