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@@ -4,12 +4,16 @@ datasets:
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  - Norquinal/claude_multiround_chat_30k
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  - OpenLeecher/Teatime
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  ---
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- We proudly announce this is the world first 128k context model based on RWKV architecture today, 2023-08-10.
 
 
 
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  With RWKV world tokenizer,multi-langs have 1:1 tokenization ratio ,one word to one token.
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  (https://github.com/BlinkDL/ChatRWKV/blob/2a13ddecd81f8fd615b6da3a8f1091a594689e30/tokenizer/rwkv_tokenizer.py#L163)
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  This model trained with instructions datasets and chinese web novel and tradition wuxia,
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  more trainning details would be updated.
@@ -21,6 +25,8 @@ https://github.com/SynthiaDL/TrainChatGalRWKV/blob/main/train_world.sh
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  ![QQ图片20230810153529.jpg](https://cdn-uploads.huggingface.co/production/uploads/6176b32847ee6431f632981e/d8ekmc4Lfhy2lYEdrRKXz.jpeg)
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  Using RWKV Runner https://github.com/josStorer/RWKV-Runner to test this model, only need 16G vram to run fp16 or 8G vram fp16i8, use temp 0.1-0.2 topp 0.7 for more precise answer ,temp between 1-2.x is more creatively.
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  ![微信截图_20230810162303.png](https://cdn-uploads.huggingface.co/production/uploads/6176b32847ee6431f632981e/Ww45-WMngl4Jyt1OZDAa_.png)
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  - Norquinal/claude_multiround_chat_30k
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  - OpenLeecher/Teatime
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  ---
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+
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+ # RWKV 7B World 128k for novel writing
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+
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+ We proudly announce this is the world first **128k context** model based on RWKV architecture today, 2023-08-10.
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  With RWKV world tokenizer,multi-langs have 1:1 tokenization ratio ,one word to one token.
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  (https://github.com/BlinkDL/ChatRWKV/blob/2a13ddecd81f8fd615b6da3a8f1091a594689e30/tokenizer/rwkv_tokenizer.py#L163)
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+ # How to train infinte context model?
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  This model trained with instructions datasets and chinese web novel and tradition wuxia,
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  more trainning details would be updated.
 
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  ![QQ图片20230810153529.jpg](https://cdn-uploads.huggingface.co/production/uploads/6176b32847ee6431f632981e/d8ekmc4Lfhy2lYEdrRKXz.jpeg)
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+ # How to Test?
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+
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  Using RWKV Runner https://github.com/josStorer/RWKV-Runner to test this model, only need 16G vram to run fp16 or 8G vram fp16i8, use temp 0.1-0.2 topp 0.7 for more precise answer ,temp between 1-2.x is more creatively.
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  ![微信截图_20230810162303.png](https://cdn-uploads.huggingface.co/production/uploads/6176b32847ee6431f632981e/Ww45-WMngl4Jyt1OZDAa_.png)
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