Create README.md

README.md

@@ -0,0 +1,37 @@
+## Model description
+T5 model trained for Grammar Correction. This model corrects grammatical mistakes in input sentences
+
+### Dataset Description
+The T5-base model has been trained on C4_200M dataset. 
+### Model in Action 🚀
+```
+import torch
+from transformers import T5Tokenizer, T5ForConditionalGeneration
+model_name = 'deep-learning-analytics/GrammarCorrector'
+torch_device = 'cuda' if torch.cuda.is_available() else 'cpu'
+tokenizer = T5Tokenizer.from_pretrained(model_name)
+model = T5ForConditionalGeneration.from_pretrained(model_name).to(torch_device)
+
+def correct_grammar(input_text,num_return_sequences):
+  batch = tokenizer([input_text],truncation=True,padding='max_length',max_length=64, return_tensors="pt").to(torch_device)
+  translated = model.generate(**batch,max_length=64,num_beams=num_beams, num_return_sequences=num_return_sequences, temperature=1.5)
+  tgt_text = tokenizer.batch_decode(translated, skip_special_tokens=True)
+  return tgt_text
+  
+```
+
+### Example Usage
+```
+text = 'He are moving here.'
+print(correct_grammar(text, num_return_sequences=2))
+['He is moving here.', 'He is moving here now.']
+```
+
+Another example
+```
+text = 'Cat drinked milk'
+print(correct_grammar(text, num_return_sequences=2))
+['Cat drank milk.', 'Cat drink milk.']
+```
+
+Model Developed by [Priya-Dwivedi](https://www.linkedin.com/in/priyanka-dwivedi-6864362)