metadata

base_model:
  - Snowflake/snowflake-arctic-embed-m-long

CodeRankEmbed

CodeRankEmbed is a 137M bi-encoder supporting 8192 context length for code retrieval. It significantly outperforms various open-source and proprietary code embedding models on various code retrieval tasks.

Performance Benchmarks

Name	Parameters	CSN	CoIR
CodeRankEmbed	137M	77.9	60.1
CodeSage-Large	1.3B	71.2	59.4
Jina-Code-v2	161M	67.2	58.4
CodeT5+	110M	74.2	45.9
Voyage-Code-002	Unknown	68.5	56.3

Usage

Important: the query prompt must include the following task instruction prefix: "Represent this query for searching relevant code"

from sentence_transformers import SentenceTransformer

model = SentenceTransformer("cornstack/CodeRankEmbed", trust_remote_code=True)
queries = ['Represent this query for searching relevant code: Calculate the n-th Fibonacci number']
codes = ["""def func(n):
    if n <= 0:
        return "Input should be a positive integer"
    elif n == 1:
        return 0
    elif n == 2:
        return 1
    else:
        a, b = 0, 1
        for _ in range(2, n):
            a, b = b, a + b
        return b
"""]
query_embeddings = model.encode(queries)
print(query_embeddings)
code_embeddings = model.encode(codes)
print(code_embeddings)