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--- |
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language: |
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- en |
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pipeline_tag: text2text-generation |
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metrics: |
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- f1 |
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tags: |
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- SQL |
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- plSQL |
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- english |
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--- |
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This is a fine-tuned version of T5 FLAN LARGE (783M) on English in particular on the public dataset spider for text-toSQL. |
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To initialize the model: |
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from transformers import T5ForConditionalGeneration |
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model = T5ForConditionalGeneration.from_pretrained("MRNH/flan-t5-large-PLsql") |
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Use the tokenizer: |
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tokenizer = T5ForConditionalGeneration.from_pretrained("MRNH/flan-t5-large-PLsql") |
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input = tokenizer("<question> "+sentence["db_id"]+" </question> "+sentence["question"], |
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text_target=sentence["query"], return_tensors='pt') |
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To generate text using the model: |
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output = model.generate(input["input_ids"],attention_mask=input["attention_mask"]) |
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Training of the model is performed using the following loss computation based on the hidden state output h: |
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h.logits, h.loss = model(input_ids=input["input_ids"], |
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attention_mask=input["attention_mask"], |
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labels=input["labels"]) |
