Instructions to use conversify/response-score with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use conversify/response-score with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="conversify/response-score")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("conversify/response-score") model = AutoModelForSequenceClassification.from_pretrained("conversify/response-score") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3ca4c447839bb321a45a1dc050b540b77b673107cfb2fefbd75b814b8b58c4fd
- Size of remote file:
- 438 MB
- SHA256:
- ea58fb2bb5c59068f77b523eabefbd70e592100ba9b70a4a3b563c7ff8ac224a
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