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from datasets import load_dataset | |
from evaluate import evaluator | |
from transformers import AutoModelForSequenceClassification, pipeline | |
import gradio as gr | |
data = load_dataset("huolongguo10/insecure",split="train").shuffle(seed=42).select(range(1000)) | |
task_evaluator = evaluator("text-classification") | |
# 1. Pass a model name or path | |
eval_results = task_evaluator.compute( | |
model_or_pipeline="huolongguo10/check_sec", | |
data=data, | |
input_column="sentence1", | |
label_mapping={"LABEL_0": 0, "LABEL_1": 1} | |
) | |
with gr.Blocks() as demo: | |
gr.JSON(eval_results) | |
print(eval_results) | |
demo.launch() |