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README.md
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Quantized versions are available from Bartowski: [GGUF](https://huggingface.co/bartowski/Pantheon-RP-1.0-8b-Llama-3-GGUF) - [EXL2](https://huggingface.co/bartowski/Pantheon-RP-1.0-8b-Llama-3-exl2)
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## Model details
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This model features a highly diverse collection of datasets, totaling ~
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- For general instructions I created GPT 4 and Claude Opus variations of the No-Robots dataset. I actually ended up not including NoRo itself as it made the model worse.
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- For roleplay I used an extensive collection of GPT 4 and Claude Opus data, augmented by the always popular LimaRP for the "human factor".
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- The Pantheon Roleplay personas were made using Claude 1.3 data, further diversifying the outputs of this model.
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- Aiva's persona includes additional datasets featuring questions related to DM world building, Python coding and RSS summarization. (She summarizes my daily news every day!)
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Roughly
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**TLDR;** Download. ChatML prompt format. Have fun! Leave feedback!
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Quantized versions are available from Bartowski: [GGUF](https://huggingface.co/bartowski/Pantheon-RP-1.0-8b-Llama-3-GGUF) - [EXL2](https://huggingface.co/bartowski/Pantheon-RP-1.0-8b-Llama-3-exl2)
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## Model details
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This model features a highly diverse collection of datasets, totaling ~24 million tokens;
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- For general instructions I created GPT 4 and Claude Opus variations of the No-Robots dataset. I actually ended up not including NoRo itself as it made the model worse.
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- For roleplay I used an extensive collection of GPT 4 and Claude Opus data, augmented by the always popular LimaRP for the "human factor".
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- The Pantheon Roleplay personas were made using Claude 1.3 data, further diversifying the outputs of this model.
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- Aiva's persona includes additional datasets featuring questions related to DM world building, Python coding and RSS summarization. (She summarizes my daily news every day!)
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Roughly 30% of the training data was instructional, with another 25% being used by the Pantheon Persona data. The remaining 45% was filled with roleplay scenarios covering a huge spectrum of situations. Each of these datasets was then carefully balanced to ensure diversity, removing examples where deemed necessary.
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**TLDR;** Download. ChatML prompt format. Have fun! Leave feedback!
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