安装环境
pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
pip install transformers
代码
question = "What are the email address, town and county of the customers who are of the least common gender?"schema = """CREATE TABLE Products ( product_id number,parent_product_id number,product_name text,product_price number,product_color text,product_size text,product_description text);CREATE TABLE Customers (customer_id number,gender_code text,customer_first_name text,customer_middle_initial text,customer_last_name text,email_address text,login_name text,login_password text,phone_number text,address_line_1 text,town_city text,county text,country text);CREATE TABLE Customer_Payment_Methods (customer_id number,payment_method_code text);CREATE TABLE Invoices (invoice_number number,invoice_status_code text,invoice_date time);CREATE TABLE Orders (order_id number,customer_id number,order_status_code text,date_order_placed time);CREATE TABLE Order_Items (order_item_id number,product_id number,order_id number,order_item_status_code text);CREATE TABLE Shipments (shipment_id number,order_id number,invoice_number number,shipment_tracking_number text,shipment_date time);CREATE TABLE Shipment_Items (shipment_id number,order_item_id number);
"""
prompt = f"""<schema>{schema}</schema>
<question>{question}</question>
<sql>"""from transformers import AutoModelForCausalLM, AutoTokenizer
device = "cuda"
model = AutoModelForCausalLM.from_pretrained("PipableAI/pip-sql-1.3b")
tokenizer = AutoTokenizer.from_pretrained("PipableAI/pip-sql-1.3b")inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=200)
print(tokenizer.decode(outputs[0], skip_special_tokens=True).split('<sql>')[1].split('</sql>')[0])输出的sql
)
