---
base_model: flair/bueble-lm-2b
license: mit
---

# BübleLM QLoRA – Grounding Act Classification

This model is a fine-tuned version of [flair/bueble-lm-2b](https://huggingface.co/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

```python
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