bge code v1 EU AI Act Compliance Profile

For more details please refer to our Github: FlagEmbedding.

BGE-Code-v1 is an LLM-based code embedding model that supports code retrieval, text retrieval, and multilingual retrieval. It primarily demonstrates the following capabilities:

• Superior Code Retrieval Performance: The model demonstrates exceptional code retrieval capabilities, supporting natural language queries in both English and Chinese, as well as 20 programming languages.
• Robust Text Retrieval Capabilities: The model maintains strong text retrieval capabilities comparable to text embedding models of similar scale.
• Extensive Multilingual Support: BGE-Code-v1 offers comprehensive multilingual retrieval capabilities, excelling in languages such as English, Chinese, Japanese, French, and more.

Usage

Using FlagEmbedding

from FlagEmbedding import FlagLLMModel
queries = [
    "Delete the record with ID 4 from the 'Staff' table.", 
    'Delete all records in the "Livestock" table where age is greater than 5'
]
documents = [
    "DELETE FROM Staff WHERE StaffID = 4;",
    "DELETE FROM Livestock WHERE age > 5;"
]
model = FlagLLMModel('BAAI/bge-code-v1', 
                     query_instruction_format="<instruct>{}\n<query>{}",
                     query_instruction_for_retrieval="Given a question in text, retrieve SQL queries that are appropriate responses to the question.",
                     trust_remote_code=True,
                     use_fp16=True) # Setting use_fp16 to True speeds up computation with a slight performance degradation
embeddings_1 = model.encode_queries(queries)
embeddings_2 = model.encode_corpus(documents)
similarity = embeddings_1 @ embeddings_2.T
print(similarity)

By default, FlagLLMModel will use all available GPUs when encoding. Please set `os.environ["CUDA_VISIBLE_DEVICE

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