metadata
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
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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)
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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.
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Sample output: 1
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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)