llm-semantic-router/Vela-1.0-Encoder-307M-Feedback
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Vela Feedback
Vela Feedback distinguishes satisfaction, clarification, reported errors, requested changes, and independent new requests.
307M parameters · Input capacity: 32,768 tokens, including special tokens.
Labels: SAT, NEED_CLARIFICATION, WRONG_ANSWER, WANT_DIFFERENT, and NO_FEEDBACK. Quoted praise or criticism is not automatically feedback.
Evaluation
Compared with the original mmBERT32K Feedback model on the same development inputs. F1 and accuracy are reported on a 0–100 scale.
Both models use FP32 and complete inputs. The development set includes authored requests, controlled long contexts and reviewed natural requests, and informed Vela selection. The original model has four labels: neutral coverage is measured separately, while Vela’s NO_FEEDBACK predictions count as errors on shared-class examples.
Quick start
With PyTorch and Transformers 4.57.6 or 5.17.0:
from transformers import pipeline
model_id = "llm-semantic-router/Vela-1.0-Encoder-307M-Feedback"
model = pipeline("text-classification", model=model_id, device=-1)
print(model("That answered my question, thank you.", top_k=None, truncation=False))