Instructions to use pedropei/question-intimacy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pedropei/question-intimacy with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="pedropei/question-intimacy")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("pedropei/question-intimacy") model = AutoModelForSequenceClassification.from_pretrained("pedropei/question-intimacy") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fad1a433b33eafe0d932e60015c5a5aadfa5db3bf086bfb7f5fd7848d396f428
- Size of remote file:
- 501 MB
- SHA256:
- 6a0a05d322eb6fc6c6b6bb4c1873f66b6982ec8fa0fa44a5ecb84c17cd303b94
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