---
base_model: mistralai/Mistral-7B-Instruct-v0.2
library_name: transformers
pipeline_tag: text-generation
tags:
- mcquilibrium
- multiple-choice
- detell
- qlora
---

# mistral-7b-detell

MCQuilibrium de-tell model. A QLoRA fine-tune of Mistral-7B-Instruct-v0.2 that rewrites the
answer choices of a multiple-choice question to remove tells, the surface artifacts that leak
the correct answer. The LoRA adapter has been merged into the base weights, so this repo loads
directly.

## Usage

```python
from transformers import AutoModelForCausalLM, AutoTokenizer

tok = AutoTokenizer.from_pretrained("ArHFcloud/mistral-7b-detell")
model = AutoModelForCausalLM.from_pretrained("ArHFcloud/mistral-7b-detell", device_map="auto")

messages = [{"role": "user", "content": "...question and choices..."}]
inputs = tok.apply_chat_template(messages, add_generation_prompt=True, return_tensors="pt").to(model.device)
out = model.generate(inputs, max_new_tokens=512)
print(tok.decode(out[0][inputs.shape[-1]:], skip_special_tokens=True))
```