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README.md ADDED
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+ ---
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+
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+
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+ frameworks:
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+
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+ - Pytorch
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+ license: other
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+ tasks:
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+ - text-generation
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+
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+ ---
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+
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+ # Model Card for NL2SQL-StarCoder-15B
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+
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+ ## 模型介绍
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+
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+ NL2SQL-StarCoder-15B 是在基础模型 StarCoder 上通过 QLoRA 对自然语言生成SQL任务进行微调的 15B Code-LLM。
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+
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+ ## Requirements
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+
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+ - python>=3.8
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+ - pytorch>=2.0.0
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+ - transformers==4.32.0
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+ - CUDA 11.4
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+ ## 推理数据格式
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+
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+ 推理数据为模型在训练数据格式下拼接的字符串形式,它也是推理时输入prompt拼接的方式:
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+ ```python
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+ """
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+ <|user|>
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+ /* Given the following database schema: */
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+ CREATE TABLE "table_name" (
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+ "col1" int,
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+ ...
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+ ...
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+ )
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+
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+ /* Write a sql to answer the following question: {问题} */
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+ <|assistant|>
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+ ```sql
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+ {输出SQL}
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+ ```<|end|>
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+ """
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+ ```
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+
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+ ## 快速开始
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+
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+ ```python
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+ import torch
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+ from modelscope import snapshot_download, AutoModelForCausalLM, AutoTokenizer,GenerationConfig
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+ model_dir = snapshot_download("iic/NL2SQL-StarCoder-15B")
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+ tokenizer = AutoTokenizer.from_pretrained(model_dir, device_map="auto",
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+ trust_remote_code=True, torch_dtype=torch.float16)
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+ tokenizer.padding_side = "left"
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+ tokenizer.pad_token_id = tokenizer.convert_tokens_to_ids("<fim_pad>")
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+ tokenizer.eos_token_id = tokenizer.convert_tokens_to_ids("<|endoftext|>")
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+ tokenizer.pad_token = "<fim_pad>"
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+ tokenizer.eos_token = "<|endoftext|>"
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+
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+ model = AutoModelForCausalLM.from_pretrained(model_dir, device_map="auto",
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+ trust_remote_code=True, torch_dtype=torch.float16)
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+ model.eval()
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+
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+ text = '<|user|>\n/* Given the following database schema: */\nCREATE TABLE "singer" (\n"Singer_ID" int,\n"Name" text,\n"Country" text,\n"Song_Name" text,\n"Song_release_year" text,\n"Age" int,\n"Is_male" bool,\nPRIMARY KEY ("Singer_ID")\n)\n\n/* Write a sql to answer the following question: Show countries where a singer above age 40 and a singer below 30 are from. */<|end|>\n'
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+ inputs = tokenizer(text, return_tensors='pt', padding=True, add_special_tokens=False).to("cuda")
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+ outputs = model.generate(
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+ inputs=inputs["input_ids"],
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+ attention_mask=inputs["attention_mask"],
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+ max_new_tokens=512,
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+ top_p=0.95,
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+ temperature=0.1,
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+ do_sample=False,
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+ eos_token_id=tokenizer.eos_token_id,
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+ pad_token_id=tokenizer.pad_token_id
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+ )
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+ gen_text = tokenizer.batch_decode(outputs[:, inputs["input_ids"].shape[1]:], skip_special_tokens=True)
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+ print(gen_text)
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+ ```
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+
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+ "_name_or_path": "./pretrained_model/",
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+ "activation_function": "gelu",
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+ "architectures": [
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+ "GPTBigCodeForCausalLM"
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+ ],
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+ "summary_first_dropout": 0.1,
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+ "summary_proj_to_labels": true,
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+ "summary_type": "cls_index",
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+ }
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+ {"framework":"Pytorch","task":"text-generation"}
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+ "<reponame>"
22
+ ],
23
+ "bos_token": "<|endoftext|>",
24
+ "eos_token": "<|endoftext|>",
25
+ "unk_token": "<|endoftext|>"
26
+ }
tokenizer.json ADDED
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tokenizer_config.json ADDED
@@ -0,0 +1,31 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_prefix_space": false,
3
+ "additional_special_tokens": [
4
+ "<|endoftext|>",
5
+ "<fim_prefix>",
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+ "<fim_middle>",
7
+ "<fim_suffix>",
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+ "<fim_pad>",
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+ "<filename>",
10
+ "<gh_stars>",
11
+ "<issue_start>",
12
+ "<issue_comment>",
13
+ "<issue_closed>",
14
+ "<jupyter_start>",
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+ "<jupyter_text>",
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+ "<jupyter_code>",
17
+ "<jupyter_output>",
18
+ "<empty_output>",
19
+ "<commit_before>",
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+ "<commit_msg>",
21
+ "<commit_after>",
22
+ "<reponame>"
23
+ ],
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+ "bos_token": "<|endoftext|>",
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+ "clean_up_tokenization_spaces": true,
26
+ "eos_token": "<|endoftext|>",
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+ "model_max_length": 1000000000000000019884624838656,
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+ "tokenizer_class": "GPT2Tokenizer",
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+ "unk_token": "<|endoftext|>",
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+ "vocab_size": 49152
31
+ }
vocab.json ADDED
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