---
library_name: peft
base_model: mistralai/Mistral-7B-v0.1
pipeline_tag: text-generation
---
Description: Multiple-choice sentence completion\
Original dataset: https://huggingface.co/datasets/Rowan/hellaswag \
---\
Try querying this adapter for free in Lora Land at https://predibase.com/lora-land! \
The adapter_category is Other and the name is Multiple Choice Sentence Completion (hellaswag)\
---\
Sample input: You are provided with an incomplete passage below as well as 4 endings in quotes and separated by commas, with only one of them being the correct ending. Treat the endings as being labelled 0, 1, 2, 3 in order. Please respond with the number corresponding to the correct ending for the passage.\n\n### Passage: The mother instructs them on how to brush their teeth while laughing. The boy helps his younger sister brush his teeth. she\n\n### Endings: ['shows how to hit the mom and then kiss his dad as well.'
 'brushes past the camera, looking better soon after.'
 'glows from the center of the camera as a reaction.'
 'gets them some water to gargle in their mouths.']\n\n### Correct Ending Number: \
---\
Sample output: 3.0\
---\
Try using this adapter yourself!
```
from transformers import AutoModelForCausalLM, AutoTokenizer

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

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