| license: mit | |
| language: de | |
| Mistral-7B German [LAPT] | |
| === | |
| ## How to use | |
| ```python | |
| from peft import AutoPeftModelForCausalLM | |
| from transformers import AutoTokenizer | |
| model = AutoPeftModelForCausalLM.from_pretrained( | |
| "atsuki-yamaguchi/Mistral-7B-v0.1-lapt-de" | |
| ) | |
| tokenizer = AutoTokenizer.from_pretrained( | |
| "mistralai/Mistral-7B-v0.1" | |
| ) | |
| # w/ GPU | |
| model = AutoPeftModelForCausalLM.from_pretrained( | |
| "atsuki-yamaguchi/Mistral-7B-v0.1-lapt-de", | |
| device_map="auto", | |
| load_in_8bit=True, | |
| ) | |
| ``` | |
| ## Citation | |
| ``` | |
| @article{yamaguchi2024empirical, | |
| title={An Empirical Study on Cross-lingual Vocabulary Adaptation for Efficient Generative {LLM} Inference}, | |
| author={Atsuki Yamaguchi and Aline Villavicencio and Nikolaos Aletras}, | |
| journal={ArXiv}, | |
| year={2024}, | |
| volume={abs/2402.10712}, | |
| url={https://arxiv.org/abs/2402.10712} | |
| } | |
| ``` | |
| ## Link | |
| For more details, please visit https://github.com/gucci-j/llm-cva | |