|
|
--- |
|
|
base_model: LSX-UniWue/LLaMmlein_7B_chat |
|
|
license: mit |
|
|
--- |
|
|
|
|
|
# LLäMmlein QLoRA – Grounding Act Classification |
|
|
|
|
|
This model is a fine-tuned version of [LSX-UniWue/LLaMmlein_7B_chat](https://huggingface.co/LSX-UniWue/LLaMmlein_7B_chat), 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) |
|
|
|
|
|
--- |
|
|
|
|
|
## Use Cases |
|
|
|
|
|
- Dialogue system analysis |
|
|
- Teacher-student interaction classification |
|
|
- Grounding in institutional advising or classroom discourse |
|
|
|
|
|
--- |
|
|
|
|
|
## How to Use |
|
|
|
|
|
```python |
|
|
from transformers import AutoModelForSequenceClassification, AutoTokenizer |
|
|
|
|
|
model = AutoModelForSequenceClassification.from_pretrained("MB55/qlora_new") |
|
|
tokenizer = AutoTokenizer.from_pretrained("MB55/qlora_new") |
|
|
|
|
|
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 |
