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  license: apache-2.0
 
 
 
 
 
 
 
 
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  ---
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  # Welcome to a new generation of Minecraft
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  ## How was model trained?
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- The dataset was made from
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  license: apache-2.0
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+ datasets:
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+ - Sweaterdog/Andy-3.5
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+ language:
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+ - en
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+ base_model:
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+ - deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
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+ tags:
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+ - Minecraft
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  ---
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  # Welcome to a new generation of Minecraft
 
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  ## How was model trained?
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+ The model was trained on a dataset of ~10,000 messages coming directly from MindCraft, ensuring quality data
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+ ## What are capabilities and Limitations?
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+ The smaller model *(The preview ones at least)* had 1/3 of the parameters tuned, the larger preview model has not been released yet.
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+ Andy-3.5 was trained on EVERYTHING regarding Minecraft and MindCraft, it knows how to use commands natively without a system prompt.
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+ Andy-3.5 also knows how to build / use !newAction to perform commands, it was trained on lots of building, as well as, using !newAction to do tasks like manually making something or strip mining.
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+
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+ ****Know this is a PREVIEW model, it is NOT finished!****
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+
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+ ## Why a preview model?
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+
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+ Andy-3.5-preview was made to test the intelligence of a Minecraft Ai with the current dataset, it was meant to see the progress of the training and what area's are needed for the future
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+ DO NOT expect this model to be able to do everything perfectly, it only knows as much as the dataset told it, as well as the other 2/3 of the untouched parameters allow.
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+ The model *may* experience bugs, such as not saying your name, getting previous messages confused, or other small things.
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+
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+ ## Important notes and considerations
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+ The preview model of Andy-3.5-mini *(Andy-3.5-mini-preview)* was trained on a context length of 4096, this was meant to speed up training and VRAM usage.
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+ The Base model of Andy-3.5-mini-preview was a distilled version of Deepseek-R1, which was a tuned model of Qwen-2.5-1.5b
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+ Since a context window of 4096 is not nearly enough for MindCraft, you can go higher, Qwen-2.5-1.5b was trained on a context length of 64,000, the distilled version of Deepseek-R1 was trained on a length of 128,000, the usable length may be closer to 32,000 tokens for Andy-3.5-mini-preview
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+ When the full versions of Andy-3.5 and Andy-3.5-preview release, they will both be trained on a context length of 128,000 to ensure proper usage during playing.