Update README.md
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README.md
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@@ -52,7 +52,7 @@ Finetuned by Mr. Yunsung Ji (Saxo), a data scientist at Linkbricks, a company sp
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CPT(Continue-Pretraining)->SFT->DPO training model based on Mistral-Nemo-Instruct-2407 through 8 H100-80Gs as a Korean language model <br>
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It is a model that has been trained to handle Korean-Chinese-English-Japanese cross-training data and 10M korean news corpus and logic judgment data for various tasks to enable cross-fertilization processing and complex Korean logic & math problems. <br>
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-Tokenizer uses the base model without word expansion<br>
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-Models enhanced with high-dimensional analysis of customer reviews and social posts, as well as coding, writing,
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-128k-Context Window<br>
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-Support for Korean Functioncall and Tool Calling<br>
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-Deepspeed Stage=3, use rslora and BAdam Layer Mode<br>
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| 52 |
CPT(Continue-Pretraining)->SFT->DPO training model based on Mistral-Nemo-Instruct-2407 through 8 H100-80Gs as a Korean language model <br>
|
| 53 |
It is a model that has been trained to handle Korean-Chinese-English-Japanese cross-training data and 10M korean news corpus and logic judgment data for various tasks to enable cross-fertilization processing and complex Korean logic & math problems. <br>
|
| 54 |
-Tokenizer uses the base model without word expansion<br>
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| 55 |
+
-Models enhanced with high-dimensional analysis of customer reviews and social posts, as well as coding, writing, math and decision making<br>
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| 56 |
-128k-Context Window<br>
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| 57 |
-Support for Korean Functioncall and Tool Calling<br>
|
| 58 |
-Deepspeed Stage=3, use rslora and BAdam Layer Mode<br>
|