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:
- b9c449f114acb4c39ece0879a7a92ad4ee63b491bde70ef00bfbe76ec5960b2b
- Size of remote file:
- 438 MB
- SHA256:
- df9682a8c80370e8a4d5a9e66558df0a39a80d830729cc1350e701b7be90210c
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