
new version: [LarkAI/codet5p-770m_nl2sql_oig](https://huggingface.co/LarkAI/codet5p-770m_nl2sql_oig)

use oig-sql dataset and support more complex sql parse

# How to Use

```python
import torch
from transformers import AutoTokenizer, BartForConditionalGeneration

device = torch.device('cuda:0')

tokenizer = AutoTokenizer.from_pretrained("LarkAI/bart_large_nl2sql")
model = BartForConditionalGeneration.from_pretrained("LarkAI/bart_large_nl2sql").to(device)

text = "question: get people name with age less 25 table: id, name, age"
inputs = tokenizer([text], max_length=1024, return_tensors="pt")
output_ids = model.generate(inputs["input_ids"].to(device), num_beams=self.beams, max_length=128, min_length=8)
response_text = tokenizer.batch_decode(output_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)[0]
# SELECT name FROM table WHERE age < 25
```

reference: [juierror/flan-t5-text2sql-with-schema](https://huggingface.co/juierror/flan-t5-text2sql-with-schema) - fix this [discussion](https://huggingface.co/juierror/flan-t5-text2sql-with-schema/discussions/5)

# How to Train

Quick start: https://github.com/huggingface/transformers/blob/main/examples/pytorch/summarization/README.md
{"language": ["en"], "license": "apache-2.0", "tags": ["nl2sql"], "datasets": ["wikisql"], "pipeline_tag": "text2text-generation", "widget": [{"text": "question: get people name with age less 25 table: id, name, age", "example_title": "less than"}, {"text": "question: get people name with age equal 25 table: id, name, age", "example_title": "equal"}]}
transformers pytorch bart feature-extraction nl2sql text2text-generation en dataset:wikisql license:apache-2.0 endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #bart #feature-extraction #nl2sql #text2text-generation #en #dataset-wikisql #license-apache-2.0 #endpoints_compatible #has_space #region-us 


new version: LarkAI/codet5p-770m_nl2sql_oig

use oig-sql dataset and support more complex sql parse

# How to Use



reference: juierror/flan-t5-text2sql-with-schema - fix this discussion

# How to Train

Quick start: URL
# How to Use



reference: juierror/flan-t5-text2sql-with-schema - fix this discussion # How to Train

Quick start: URL
TAGS
#transformers #pytorch #bart #feature-extraction #nl2sql #text2text-generation #en #dataset-wikisql #license-apache-2.0 #endpoints_compatible #has_space #region-us 
 # How to Use



reference: juierror/flan-t5-text2sql-with-schema - fix this discussion # How to Train

Quick start: URL