---
library_name: peft
base_model: mistralai/Mistral-7B-v0.1
pipeline_tag: text-generation
---
Description: Binary sentiment detection\
Original dataset: https://huggingface.co./datasets/glue/viewer/sst2 \
---\
Try querying this adapter for free in Lora Land at https://predibase.com/lora-land! \
The adapter_category is Sentiment Detection and the name is Sentiment Detection (SST2)\
---\
Sample input: Given the following sentence:\n\nthis illuminating documentary transcends our preconceived vision of the holy land and its inhabitants , revealing the human complexities beneath . \n\nRespond with 0 if the sentiment of the sentence is negative and 1 if the sentiment of the sentence is positive.\
---\
Sample output: 1\
---\
Try using this adapter yourself!
```
from transformers import AutoModelForCausalLM, AutoTokenizer

model_id = "mistralai/Mistral-7B-v0.1"
peft_model_id = "predibase/glue_sst2"

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