How to use shubharuidas/codebert-base-code-embed-mrl-langchain-langgraph with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("shubharuidas/codebert-base-code-embed-mrl-langchain-langgraph") sentences = [ "Best practices for __init__", "def close(self) -> None:\n self.sync()\n self.clear()", "class MyClass:\n def __call__(self, state):\n return\n\n def class_method(self, state):\n return", "def __init__(self, name: str):\n self.name = name\n self.lock = threading.Lock()" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
