Instructions to use t-bank-ai/response-quality-classifier-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use t-bank-ai/response-quality-classifier-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="t-bank-ai/response-quality-classifier-base") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("t-bank-ai/response-quality-classifier-base") model = AutoModelForSequenceClassification.from_pretrained("t-bank-ai/response-quality-classifier-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4354f770d8c0f0bb4a126e4db956a8d105d997754c3fb1ea0aad8e6b5b1afecb
- Size of remote file:
- 712 MB
- SHA256:
- 6d6f0385f4ab87c1ad734824c1179ff37850e189799be001f989231cd5c6b413
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