Text Generation
GGUF
English
Chinese
MOE
Qwen 2.5 MOE
Mixture of Experts
6X1.5B
deepseek
reasoning
thinking
creative
128k context
general usage
problem solving
brainstorming
solve riddles
story generation
plot generation
storytelling
fiction story
story
writing
fiction
Qwen 2.5
mergekit
Inference Endpoints
conversational
Update README.md
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README.md
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<H2>Qwen2.5-MOE-6x1.5B-DeepSeek-Reasoning-e32-gguf</H2>
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This is a highly experimental Qwen2.5 MOE (Mixture of Experts) model comprised of SIX Qwen 2.5 1.5B models.
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It includes the following models:
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In Lmstudio the "Jinja Template" should load by default.
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In other apps - use the Deepseek Tokenizer.
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Sometimes this model will output/think in Chinese Characters/Symbols (with an English prompt) - regen to clear.
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Likewise, because these are small models, it may do a tonne of "thinking"/"reasoning" and then "forget" to finish a / the task(s). In
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this case, prompt the model to "Complete the task XYZ with the 'reasoning plan' above" .
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Also set context limit at 4k minimum, 8K+ suggested.
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<H2>Qwen2.5-MOE-6x1.5B-DeepSeek-Reasoning-e32-gguf</H2>
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This is a highly experimental Qwen2.5 MOE (Mixture of Experts) model comprised of SIX Qwen 2.5 1.5B models creating a 8.71B model.
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This model can be used for all use cases, and is also (mostly) uncensored.
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It includes the following models:
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In Lmstudio the "Jinja Template" should load by default.
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In other apps - use the Deepseek Tokenizer and/or "Jinja Template".
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Sometimes this model will output/think in Chinese Characters/Symbols (with an English prompt) - regen to clear.
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Likewise, because these are small models, it may do a tonne of "thinking"/"reasoning" and then "forget" to finish a / the task(s). In
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this case, prompt the model to "Complete the task XYZ with the 'reasoning plan' above" .
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Likewise it may function better if you breakdown the reasoning/thinking task(s) into smaller pieces :
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"IE: Instead of asking for 6 plots FOR theme XYZ, ASK IT for ONE plot for theme XYZ at a time".
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Also set context limit at 4k minimum, 8K+ suggested.
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