Update README.md

README.md

@@ -40,4 +40,21 @@ The following hyperparameters were used during training:
 - Tokenizers 0.13.3
 
 ### Machine Used and time taken
-- RTX 3090: 8 hrs. 35 mins.
+- RTX 3090: 8 hrs. 35 mins.
+
+```python
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+
+model = AutoModelForSeq2SeqLM.from_pretrained("shorthillsai/flan-t5-large-absa", device_map="auto")
+tokenizer = AutoTokenizer.from_pretrained("shorthillsai/flan-t5-large-absa", truncation=True)
+
+prompt = """Find the aspect based sentiment for the given review. 'Not present' if the aspect is absent.\n\nReview:I love the screen of this laptop and the battery life is amazing.\n\nAspect:Battery Life\n\nSentiment: """
+
+input_ids = tokenizer(prompt, return_tensors="pt").to("cuda").input_ids
+instruct_model_outputs = instruct_model.generate(input_ids=input_ids)
+instruct_model_text_output = tokenizer.decode(instruct_model_outputs[0], skip_special_tokens=True)
+```
+
+You can then use the pipeline to answer instructions:
+
+```python