embedding_model/evaluation/models_50/gemma_embed_train.py
2025-11-12 15:02:02 +00:00

17 lines
671 B
Python

from sentence_transformers import SentenceTransformer
class model():
def __init__(self):
from sentence_transformers import SentenceTransformer
# self.model = SentenceTransformer("./models/gemma/checkpoint-33246")
self.model = SentenceTransformer("google/embeddinggemma-300m")
self.model.load_adapter("./models/gemma/checkpoint-33246")
def run(self, question:str, chunk:str)->int:
query_embeddings = self.model.encode_query(question)
document_embeddings = self.model.encode_document(chunk)
similarities = self.model.similarity(query_embeddings, document_embeddings)
return similarities