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@@ -18,15 +18,14 @@ license: cc-by-nc-4.0
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  This HF repository hosts instruction fine-tuned multilingual BLOOM model using the parallel instruction dataset called Bactrain-X in 52 languages.
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  We progressively add a language during instruction fine-tuning at each time, and train 52 models in total. Then, we evaluate those models in three multilingual benchmarks.
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- Please refer to our paper for more details.
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- #### Instruction tuning details
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  * Base model: [BLOOM 7B1](https://huggingface.co/bigscience/bloom-7b1)
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  * Instruction languages: English
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  * Instruction language codes: en
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  * Training method: full-parameter fine-tuning.
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- #### Usage
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  The model checkpoint should be loaded using `transformers` library.
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  ```python
@@ -36,9 +35,15 @@ tokenizer = AutoTokenizer.from_pretrained("MaLA-LM/lucky52-bloom-7b1-no-1")
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  model = AutoModelForCausalLM.from_pretrained("MaLA-LM/lucky52-bloom-7b1-no-1")
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  ```
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- #### Citation
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  ```
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- @article{
 
 
 
 
 
 
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  }
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  ```
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  This HF repository hosts instruction fine-tuned multilingual BLOOM model using the parallel instruction dataset called Bactrain-X in 52 languages.
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  We progressively add a language during instruction fine-tuning at each time, and train 52 models in total. Then, we evaluate those models in three multilingual benchmarks.
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+ Please refer to [our paper](https://arxiv.org/abs/2404.04850) for more details.
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  * Base model: [BLOOM 7B1](https://huggingface.co/bigscience/bloom-7b1)
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  * Instruction languages: English
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  * Instruction language codes: en
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  * Training method: full-parameter fine-tuning.
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+ ### Usage
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  The model checkpoint should be loaded using `transformers` library.
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  ```python
 
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  model = AutoModelForCausalLM.from_pretrained("MaLA-LM/lucky52-bloom-7b1-no-1")
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  ```
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+ ### Citation
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  ```
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+ @misc{lucky52,
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+ title = "Lucky 52: How Many Languages Are Needed to Instruction Fine-Tune Large Language Models?",
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+ author = "Shaoxiong Ji and Pinzhen Chen",
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+ year = "2024",
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+ eprint = "2404.04850",
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+ archiveprefix = "arXiv",
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+ primaryclass = "cs.CL"
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  }
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  ```
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