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base_model: flair/bueble-lm-2b |
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license: mit |
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# BübleLM QLoRA – Grounding Act Classification |
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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: |
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- **advance**: Contribution that moves the dialogue forward (e.g. confirmations, follow-ups, elaborations) |
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- **non_advance**: Other utterances (e.g. vague responses, misunderstandings, irrelevant comments) |
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## Use Cases |
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- Dialogue system analysis |
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- Teacher-student interaction classification |
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- Grounding in institutional advising or classroom discourse |
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--- |
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## How to Use |
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```python |
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from transformers import AutoModelForSequenceClassification, AutoTokenizer |
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model = AutoModelForSequenceClassification.from_pretrained("MB55/bueble-classifier") |
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tokenizer = AutoTokenizer.from_pretrained("MB55/bueble-classifier") |
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inputs = tokenizer("Can you explain it again?", return_tensors="pt") |
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outputs = model(**inputs) |
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prediction = outputs.logits.argmax(dim=-1) |
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print(prediction) # 0 = non_advance, 1 = advance |
