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# t5_wikisql_SQL2en
---
language: en
datasets:
- wikisql
---
[Googles T5](https://ai.googleblog.com/2020/02/exploring-transfer-learning-with-t5.html) fine-tuned on [WikiSQL](https://github.com/salesforce/WikiSQL) for **English** to **SQL** **translation**.
This is a [t5-small] (https://ai.googleblog.com/2020/02/exploring-transfer-learning-with-t5.html) fine-tuned version on the [wikisql dataset] (https://huggingface.co/datasets/wikisql).
The model can be loaded like so:
```python
from transformers import AutoTokenizer, AutoModelWithLMHead
tokenizer = AutoTokenizer.from_pretrained("dbernsohn/t5_wikisql_SQL2en")
model = AutoModelWithLMHead.from_pretrained("dbernsohn/t5_wikisql_SQL2en")
```
You can then use this model to translate SQL queries into plain english.
```python
query = "SELECT COUNT Params from model where location=HF-Hub"
input_text = f"translate English to SQL: {query} </s>"
features = tokenizer([input_text], return_tensors='pt')
output = model.generate(input_ids=features['input_ids'].cuda(),
attention_mask=features['attention_mask'].cuda())
tokenizer.decode(output[0])
```
The whole training process and hyperparameters are in my [GitHub repo] (https://github.com/DorBernsohn) |