NL2Cypher-lora is mainly fine-tuned for the Neo4j graph database, converting natural language query into the Cypher query language. It is trained for 4000 steps on a 4090 GPU. Given the limited work and possibly suboptimal performance in this area, we kindly ask for your understanding：).

快速使用NL2Cypher-lora（Quick Start with NL2Cypher-lora）

python

import os
from dataclasses import dataclass, field
from typing import Optional
import torch
import tyro
from accelerate import Accelerator
from datasets import load_dataset
from peft import  LoraConfig
from tqdm import tqdm
from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig, TrainingArguments

from trl import SFTTrainer
from trl.import_utils import is_xpu_available
from trl.trainer import ConstantLengthDataset

bnb_config = BitsAndBytesConfig(
    load_in_4bit=True,
    bnb_4bit_quant_type="nf4",
    bnb_4bit_compute_dtype=torch.bfloat16,
)

base_model = AutoModelForCausalLM.from_pretrained(
        "path/to/this/model",
        quantization_config=bnb_config,
        load_in_8bit=True,
        torch_dtype=torch.float16,
        device_map={"": "cuda:0"},
        trust_remote_code=True
)

tokenizer = AutoTokenizer.from_pretrained("path/to/this/tokenizer", use_fast=False, trust_remote_code=True)



input_text =  """
    你是一个知识图谱领域的专家，给你一个query你就可以返回一个准确的cypher，比如：
    query:"想要5个在体育人物韩献熙的4层关系内的个人介绍？" cypher:"""

input_ids = tokenizer(input_text, return_tensors="pt").to('cuda:0')

# 生成文本
output = base_model.generate(**input_ids,num_beams=10,max_new_tokens=200, repetition_penalty=1.1)

print(tokenizer.decode(output.cpu()[0], skip_special_tokens=True).split("cypher:")[1][1:])

输出为：

The output may be:

  match (n:ENTITY{name:'韩献熙'})-[*1..4]->(x) where x.name<>'体育人物' return distinct x.name limit 5

具体训练代码会稍后开源，感谢关注！

My specific training details will be open-sourced on GitHub. Enjoy my toy work.

EasonLiZZ/NL2Cypher-lora

NL2Cypher-lora介绍（Introduction to NL2Cypher-lora）

NL2Cypher-lora简介（Overview of NL2Cypher-lora）

快速使用NL2Cypher-lora（Quick Start with NL2Cypher-lora）

EasonLiZZ/
NL2Cypher-lora