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README.md

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 WangChanLion is a Multilingual, instruction-finetuned on Southeast Asian Languages SEA-LION 7B using open-source, commercially permissible datasets sample from LAION OIG chip2 and infill_dbpedia, DataBricks Dolly v2, OpenAI TL;DR, Hello-SimpleAI HC3, dolphin, iapp_wiki_qa_squad, thaisum, xlsum, scb_mt_enth_2020, han dataset, xp3x and Open-Platypus, a total of ~500k samples. Non-commercial datasets were filtered out. Released under apache 2.0 license. The models are trained to perform a subset of instruction-following tasks we found most relevant: reading comprehension, brainstorming, and creative writing. In this model, we focus on Thai and English datasets. We perform Vicuna-style evaluation using human evaluation. In a similar manner to Dolly v2, we only use open-source, commercially permissive pretrained models and datasets. Our models are neither restricted by non-commercial clauses like LLaMA-based models nor non-compete clauses like models that use self-instruct datasets from ChatGPT.
 
-Developers: PyThaiNLP and VISTEC-depa AI Research Institute of Thailand
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-Model type: SEA-LION 7B (MPT architecture)
+- Developers: PyThaiNLP and VISTEC-depa AI Research Institute of Thailand
+- Model type: SEA-LION 7B (MPT architecture)
 
 ## Model Sources
-Repository:  https://github.com/vistec-AI/WangchanLion
-Demo: [demo_WangchanLion.ipynb - Colaboratory](https://colab.research.google.com/drive/1y_7oOU3ZJI0h4chUrXFL3K4kelW_OI2G?usp=sharing#scrollTo=4yN3Bo6iAH2L)
+- Repository:  https://github.com/vistec-AI/WangchanLion
+- Demo: [demo_WangchanLion.ipynb - Colaboratory](https://colab.research.google.com/drive/1y_7oOU3ZJI0h4chUrXFL3K4kelW_OI2G?usp=sharing#scrollTo=4yN3Bo6iAH2L)
 
 # Direct Use
 Intended to be used as an instruction-following model for reading comprehension, brainstorming, and creative writing.