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README.md
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- ggml
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- causal-lm
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- gpt2
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license: mit
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---
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/6251b9851842c08ef3111c4f/NtCV4dSUaHb7XnMYrm1iF.png)
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- 2019 AI Dungeon users may recognize this model as the same one that powered [the open-source AI Dungeon 2 project](https://github.com/Latitude-Archives/AIDungeon) and its various forks. This was before AI Dungeon 2 moved to its own website and consequently rebranded to "AI Dungeon".
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- 2020-2021 AI Dungeon users may recognize this model as "Classic", the free tier below Griffin (free, but later used "energy") and Dragon (subscription).
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- If you want a better model trained on the same dataset at the cost of higher hardware requirements, check out [Spring Dragon 13B](https://huggingface.co/TheBloke/Spring-Dragon-GGUF), intended to replicate 2020 AI Dungeon's "Dragon" experience on local hardware.
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**Notes:**
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- KoboldCpp [[bfc696f]](https://github.com/LostRuins/koboldcpp/tree/bfc696fcc452975dbe8967c39301ba856d04a030) was tested without OpenBLAS.
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- ggml
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- causal-lm
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- gpt2
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- text-generation
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license: mit
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---
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/6251b9851842c08ef3111c4f/NtCV4dSUaHb7XnMYrm1iF.png)
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- 2019 AI Dungeon users may recognize this model as the same one that powered [the open-source AI Dungeon 2 project](https://github.com/Latitude-Archives/AIDungeon) and its various forks. This was before AI Dungeon 2 moved to its own website and consequently rebranded to "AI Dungeon".
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- 2020-2021 AI Dungeon users may recognize this model as "Classic", the free tier below Griffin (free, but later used "energy") and Dragon (subscription).
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- If you want a better model trained on the same dataset at the cost of higher hardware requirements, check out [Spring Dragon 13B](https://huggingface.co/TheBloke/Spring-Dragon-GGUF), intended to replicate 2020 AI Dungeon's "Dragon" experience on local hardware.
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- The motivation behind these quantizations was that [Henk717/ai-dungeon2-classic-ggml](https://huggingface.co/Henk717/ai-dungeon2-classic-ggml) was older and lacked other quantization formats. The workflow for this quantization was also different: henk717's mentions being converted to a 16-bit Pytorch checkpoint before being converted to GGML. This one was converted straight from Tensorflow to 16-bit GGML before being quantized.
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**Notes:**
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- KoboldCpp [[bfc696f]](https://github.com/LostRuins/koboldcpp/tree/bfc696fcc452975dbe8967c39301ba856d04a030) was tested without OpenBLAS.
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