Update README.md

README.md

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 # 1. Model Introduction
 
-- Orion-14B-Chat is fine-tuned from Orion-14B-Base using a high-quality corpus of approximately 850,000 entries (only sft), and it also supports Chinese, English, Japanese, and Korean. It performs exceptionally well on the MT-Bench and AlignBench evaluation sets, significantly surpassing other models of the same parameter scale in multiple metrics. For details, please refer to [tech report](https://github.com/OrionStarAI/Orion/blob/master/doc/Orion14B_v3.pdf).
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-- The 850,000 fine-tuning corpus comprises two parts: approximately 220,000 manually curated high-quality datasets and 630,000 entries selected and semantically deduplicated from open-source data through model filtering. Among these, the Japanese and Korean data, totaling 70,000 entries, have only undergone basic cleaning and deduplication.
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-- The Orion-14B series models exhibit the following features:
-  - Among models with 20B-parameter scale level, Orion-14B-Base model shows outstanding performance in comprehensive evaluations.
-  - Strong multilingual capabilities, significantly outperforming in Japanese and Korean testsets.
-  - The fine-tuned models demonstrate strong adaptability, excelling in human-annotated blind tests.
-  - The long-chat version supports extremely long texts, extending up to 200K tokens.
-  - The quantized versions reduce model size by 70%, improve inference speed by 30%, with performance loss less than 1%.
+- Orion-14B-Chat-Int4 is quantized using awq from Orion-14B-Chat while reducing model size by 70% and improving inference speed by 30%, with performance loss less than 1%.
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