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README.md

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+
+---
+library_name: transformers
+pipeline_tag: text-generation
+language:
+- multilingual
+tags:
+- generation
+- question answering
+- instruction tuning
+datasets:
+- MBZUAI/Bactrian-X
+license: cc-by-nc-4.0
+---
+
+###  Model Description
+
+This HF repository hosts instruction fine-tuned multilingual BLOOM model using the parallel instruction dataset called Bactrain-X in 52 languages. 
+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. 
+
+Please refer to our paper for more details.
+
+#### Instruction tuning details
+* Base model: [BLOOM 7B1](https://huggingface.co/bigscience/bloom-7b1)
+* Instruction languages: English, Chinese, Afrikaans, Arabic, Azerbaijani, Bengali, Czech, German, Spanish, Estonian, Farsi, Finnish, French, Galician, Gujarati, Hebrew, Hindi, Croatian, Indonesian, Italian, Japanese, Georgian, Kazakh, Khmer, Korean, Lithuanian, Latvian, Macedonian, Malayalam, Mongolian, Marathi, Burmese, Nepali, Dutch, Polish, Pashto, Portuguese, Romanian, Russian, Sinhala, Slovenian, Swedish, Swahili, Tamil, Telugu
+* Instruction language codes: en, zh, af, ar, az, bn, cs, de, es, et, fa, fi, fr, gl, gu, he, hi, hr, id, it, ja, ka, kk, km, ko, lt, lv, mk, ml, mn, mr, my, ne, nl, pl, ps, pt, ro, ru, si, sl, sv, sw, ta, te
+* Training method: full-parameter fine-tuning.
+
+#### Usage
+The model checkpoint should be loaded using `transformers` library.
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+tokenizer = AutoTokenizer.from_pretrained("MaLA-LM/lucky52-bloom-7b1-no-45")
+model = AutoModelForCausalLM.from_pretrained("MaLA-LM/lucky52-bloom-7b1-no-45")
+```
+
+#### Citation
+```
+@article{
+}
+```
+