Create mini_llm_perplexity.py

prompt_injection/evaluators/mini_llm_perplexity.py

@@ -0,0 +1,17 @@
+from prompt_injection.evaluators.base import PromptEvaluator
+from sentence_transformers import SentenceTransformer
+import numpy as np
+
+class MiniLMEmbeddingPromptEvaluator(PromptEvaluator):
+    def __init__(self) -> None:
+       super().__init__()
+       self.model=SentenceTransformer('sentence-transformers/all-MiniLM-L12-v2')
+    def eval_sample(self,sample):
+        try:
+          return self.model.encode([sample])
+        except Exception as err:
+          return np.nan
+
+
+    def get_name(self):
+        return 'Embedding'