Update README.md

README.md

@@ -17,7 +17,7 @@ datasets:
 ---
 
 # Model
-This model utilises T5-base sentence correction pre-trained model. It was fine tuned using a modified version of the [JFLEG](https://arxiv.org/abs/1702.04066) dataset and [Happy Transformer framework](https://github.com/EricFillion/happy-transformer). This model was pre-trained for educational purposes only for correction on local caribbean dialect. 
+This model utilises T5-base sentence correction pre-trained model. It was fine tuned using a modified version of the [JFLEG](https://arxiv.org/abs/1702.04066) dataset and [Happy Transformer framework](https://github.com/EricFillion/happy-transformer). This model was pre-trained for educational purposes only for correction on local Caribbean dialect. For more on Caribbean dialect checkout the library [Caribe](https://pypi.org/project/Caribe/).
 .
 ___
 
@@ -47,4 +47,24 @@ if(correction.text.find(" .")):
 
 print(correction.text) # Correction: "What is your name?".
 
-```
+```
+_
+# Usage with Transformers
+
+```python
+
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+
+tokenizer = AutoTokenizer.from_pretrained("KES/T5-KES")
+
+model = AutoModelForSeq2SeqLM.from_pretrained("KES/T5-KES")
+
+text = "I am lived with my parenmts "
+inputs = tokenizer("grammar:"+text, truncation=True, return_tensors='pt')
+
+output = model.generate(inputs['input_ids'], num_beams=4, max_length=512, early_stopping=True)
+correction=tokenizer.batch_decode(output, skip_special_tokens=True)
+print("".join(correction)) #Correction: I am living with my parents.
+
+```
+