Instructions to use microsoft/DialogRPT-human-vs-machine with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/DialogRPT-human-vs-machine with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="microsoft/DialogRPT-human-vs-machine")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("microsoft/DialogRPT-human-vs-machine") model = AutoModelForSequenceClassification.from_pretrained("microsoft/DialogRPT-human-vs-machine", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 19177168ba2b81fa32994701aed5b4469124693486b09b52406e012bc516db9c
- Size of remote file:
- 1.52 GB
- SHA256:
- bc0da6ab3fbff11b0acfa01b97a0b28211b7c40f865471c87723238e5024a602
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