Update README.md

README.md

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 ---
 license: apache-2.0
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+
+Out repository [flan-alpaca-lora](https://github.com/Reason-Wang/flan-alpaca-lora) contains the details to train flan-t5 with [Alpaca](https://github.com/tatsu-lab/stanford_alpaca) instructions and [low-rank adaptation](https://arxiv.org/abs/2106.09685). 
+
+You can use the following code easily.
+
+Usage:
+
+```python
+import transformers
+from peft import PeftModel
+import torch
+
+model_name = "google/flan-t5-xxl"; peft_model_id = "reasonwang/flan-alpaca-lora-xxl"
+tokenizer = transformers.AutoTokenizer.from_pretrained(model_name)
+base_model = transformers.AutoModelForSeq2SeqLM.from_pretrained(model_name, use_cache=False, load_in_8bit=True, torch_dtype=torch.float16, device_map={"": 0})
+peft_model = PeftModel.from_pretrained(base_model, peft_model_id, device_map={"": 0})
+
+inputs = tokenizer("List a few tips to get good scores in math.", return_tensors="pt")
+for k, v in inputs.items():
+    inputs[k] = v.to("cuda")
+outputs = peft_model.generate(**inputs, max_length=128, do_sample=True)
+print(tokenizer.batch_decode(outputs, skip_special_tokens=True))
+
+```