---
library_name: peft
base_model: mistralai/Mistral-7B-v0.1
pipeline_tag: text-generation
---
Description: Do the questions have the same meaning?\
Original dataset: https://huggingface.co/datasets/glue/viewer/qqp \
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Try querying this adapter for free in Lora Land at https://predibase.com/lora-land! \
The adapter_category is Academic Benchmarks and the name is Question Comparison (QQP)\
---\
Sample input: You are given two questions below, Question 1 and Question 2. If the two questions are semantically equivalent, please return 1. Otherwise, please return 0.\n\n### Question 1: How do I buy used car in India?\n\n### Question 2: Which used car should I buy in India?\n\n### Label: \
---\
Sample output: 0\
---\
Try using this adapter yourself!
```
from transformers import AutoModelForCausalLM, AutoTokenizer

model_id = "mistralai/Mistral-7B-v0.1"
peft_model_id = "predibase/glue_qqp"

model = AutoModelForCausalLM.from_pretrained(model_id)
model.load_adapter(peft_model_id)
```