MB55/bueble-classifier

BübleLM QLoRA – Grounding Act Classification

This model is a fine-tuned version of flair/bueble-lm-2b, optimized using QLoRA for efficient binary classification of German dialogue utterances into:

• advance: Contribution that moves the dialogue forward (e.g. confirmations, follow-ups, elaborations)
• non_advance: Other utterances (e.g. vague responses, misunderstandings, irrelevant comments)

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Use Cases

• Dialogue system analysis
• Teacher-student interaction classification
• Grounding in institutional advising or classroom discourse

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How to Use

from transformers import AutoModelForSequenceClassification, AutoTokenizer

model = AutoModelForSequenceClassification.from_pretrained("MB55/bueble-classifier")
tokenizer = AutoTokenizer.from_pretrained("MB55/bueble-classifier")

inputs = tokenizer("Can you explain it again?", return_tensors="pt")
outputs = model(**inputs)
prediction = outputs.logits.argmax(dim=-1)

print(prediction)  # 0 = non_advance, 1 = advance