| 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 \ | |
| ---\ | |
| 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) | |
| ``` |