Text Classification
Transformers
Safetensors
English
modernbert
dissatisfaction
user-feedback
conversational-ai
semantic-routing
sentiment
text-embeddings-inference
Instructions to use llm-semantic-router/feedback-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use llm-semantic-router/feedback-detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="llm-semantic-router/feedback-detector")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("llm-semantic-router/feedback-detector") model = AutoModelForSequenceClassification.from_pretrained("llm-semantic-router/feedback-detector") - Notebooks
- Google Colab
- Kaggle