This is the official repository of the paper: SPA: Towards A Computational Friendly Cloud-Base and On-Devices Collaboration Seq2seq Personalized Generation.
- Prepare well for your dataset, adjust it to the form:
{"instruction":... ,"input": ... , "output": ...}
- clone the repo
git clone [email protected]:OceannTwT/ra-isf.git
-
replace the code on LlamaForCausalLM with model/modeling_SPA.py
-
add your dataset on SPA/data/dataset_info.json
-
tune and get the SPA model!
bash train.sh
- inference the model by running llama_SPA_predict.py, remember change the dir on your additional parameters.
- This repository is served for on-devices personalized LLMs, it could contribute to fast and reliable on-devices LLMs.
- We thank for the contributions of all co-authors and siri-china teams in this work.