Create README.md

README.md

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