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README.md

@@ -1,35 +1,9 @@
 ---
-license: mit
-language:
-- de
+library_name: peft
 ---
-BLOOM-1B LAPT + Randon German
-===
+## Training procedure
 
-## How to use
-```python
-from peft import AutoPeftModelForCausalLM
-from transformers import AutoTokenizer
+### Framework versions
 
-model = AutoPeftModelForCausalLM.from_pretrained(
-  "atsuki-yamaguchi/bloom-1b1-random-de"
-)
-tokenizer = AutoTokenizer.from_pretrained(
-  "atsuki-yamaguchi/bloom-1b1-random-de"
-)
-```
 
-## 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
+- PEFT 0.5.0