Out repository flan-alpaca-lora contains the details to train flan-t5 with Alpaca instructions and low-rank adaptation.
You can use the following code easily.
Usage:
import transformers
from peft import PeftModel
model_name = "google/flan-t5-large"; peft_model_id = "reasonwang/flan-alpaca-lora-large"
tokenizer = transformers.AutoTokenizer.from_pretrained(model_name)
base_model = transformers.AutoModelForSeq2SeqLM.from_pretrained(model_name)
peft_model = PeftModel.from_pretrained(base_model, peft_model_id)
inputs = tokenizer("List a few tips to get good scores in math.", return_tensors="pt")
outputs = peft_model.generate(**inputs, max_length=128, do_sample=True)
print(tokenizer.batch_decode(outputs, skip_special_tokens=True))
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