Commit
·
6644ecd
1
Parent(s):
2330c43
commit from gujiakai
Browse files- .gitattributes +35 -35
- README.md +79 -0
- config.json +39 -0
- configuration.json +1 -0
- generation_config.json +6 -0
- pytorch_model-00001-of-00004.bin +3 -0
- pytorch_model-00002-of-00004.bin +3 -0
- pytorch_model-00003-of-00004.bin +3 -0
- pytorch_model-00004-of-00004.bin +3 -0
- pytorch_model.bin.index.json +492 -0
- special_tokens_map.json +26 -0
- tokenizer.json +0 -0
- tokenizer_config.json +31 -0
- vocab.json +0 -0
.gitattributes
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README.md
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---
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frameworks:
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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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# Model Card for NL2SQL-StarCoder-15B
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## 模型介绍
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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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## Requirements
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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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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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/* 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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## 快速开始
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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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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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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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config.json
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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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"attention_softmax_in_fp32": true,
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"attn_pdrop": 0.1,
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"bos_token_id": 0,
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"embd_pdrop": 0.1,
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"eos_token_id": 0,
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"inference_runner": 0,
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"initializer_range": 0.02,
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"layer_norm_epsilon": 1e-05,
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"max_batch_size": null,
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"max_sequence_length": null,
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"model_type": "gpt_bigcode",
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"multi_query": true,
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"n_embd": 6144,
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"n_head": 48,
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"n_inner": 24576,
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"n_layer": 40,
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"n_positions": 8192,
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"pad_key_length": true,
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"pre_allocate_kv_cache": false,
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"resid_pdrop": 0.1,
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"scale_attention_softmax_in_fp32": true,
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"scale_attn_weights": true,
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"summary_activation": null,
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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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"summary_use_proj": true,
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"torch_dtype": "float16",
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"transformers_version": "4.28.1",
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"use_cache": true,
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"validate_runner_input": true,
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"vocab_size": 49152
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}
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configuration.json
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{"framework":"Pytorch","task":"text-generation"}
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generation_config.json
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{
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"_from_model_config": true,
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"bos_token_id": 0,
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"eos_token_id": 0,
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"transformers_version": "4.28.1"
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}
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pytorch_model-00001-of-00004.bin
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pytorch_model-00002-of-00004.bin
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pytorch_model-00003-of-00004.bin
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pytorch_model.bin.index.json
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|
492 |
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special_tokens_map.json
ADDED
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{
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|
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"<|endoftext|>",
|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
tokenizer.json
ADDED
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tokenizer_config.json
ADDED
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+
{
|
2 |
+
"add_prefix_space": false,
|
3 |
+
"additional_special_tokens": [
|
4 |
+
"<|endoftext|>",
|
5 |
+
"<fim_prefix>",
|
6 |
+
"<fim_middle>",
|
7 |
+
"<fim_suffix>",
|
8 |
+
"<fim_pad>",
|
9 |
+
"<filename>",
|
10 |
+
"<gh_stars>",
|
11 |
+
"<issue_start>",
|
12 |
+
"<issue_comment>",
|
13 |
+
"<issue_closed>",
|
14 |
+
"<jupyter_start>",
|
15 |
+
"<jupyter_text>",
|
16 |
+
"<jupyter_code>",
|
17 |
+
"<jupyter_output>",
|
18 |
+
"<empty_output>",
|
19 |
+
"<commit_before>",
|
20 |
+
"<commit_msg>",
|
21 |
+
"<commit_after>",
|
22 |
+
"<reponame>"
|
23 |
+
],
|
24 |
+
"bos_token": "<|endoftext|>",
|
25 |
+
"clean_up_tokenization_spaces": true,
|
26 |
+
"eos_token": "<|endoftext|>",
|
27 |
+
"model_max_length": 1000000000000000019884624838656,
|
28 |
+
"tokenizer_class": "GPT2Tokenizer",
|
29 |
+
"unk_token": "<|endoftext|>",
|
30 |
+
"vocab_size": 49152
|
31 |
+
}
|
vocab.json
ADDED
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|
|