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Epos-8B is an 8 billion parameter language model fine-tuned for storytelling and narrative tasks. Inspired by the grandeur of epic tales, it is designed to produce high-quality, engaging content that evokes the depth and imagination of ancient myths and modern storytelling traditions.
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- **Developed by:** P0x0
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- **Funded by:**
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- **Shared by:** P0x0
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- **Model type:** Transformer-based Language Model
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- **Language(s) (NLP):** Primarily English
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Epos-8B is ideal for:
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- **Storytelling:** Generate detailed, immersive, and engaging narratives.
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- **Dialogue Creation:** Create realistic and dynamic character interactions for stories or games.
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- **Descriptive Writing:** Generate vivid descriptions for settings, objects, or events.
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- **Creative Content Generation:** Assist writers and creators in brainstorming and drafting ideas.
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### Out-of-Scope Use
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Epos-8B is not recommended for real-time decision-making, safety-critical applications, or generating harmful, biased, or inappropriate content. It is designed specifically for creative writing and narrative tasks.
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## How to Get Started with the Model
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To run the quantized version of the model, you can use [KoboldCPP](https://github.com/LostRuins/koboldcpp), which allows you to run quantized GGUF models locally.
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Epos-8B is an 8 billion parameter language model fine-tuned for storytelling and narrative tasks. Inspired by the grandeur of epic tales, it is designed to produce high-quality, engaging content that evokes the depth and imagination of ancient myths and modern storytelling traditions.
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- **Developed by:** P0x0
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- **Funded by:** P0x0
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- **Shared by:** P0x0
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- **Model type:** Transformer-based Language Model
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- **Language(s) (NLP):** Primarily English
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Epos-8B is ideal for:
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- **Storytelling:** Generate detailed, immersive, and engaging narratives.
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- **Dialogue Creation:** Create realistic and dynamic character interactions for stories or games.
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## How to Get Started with the Model
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To run the quantized version of the model, you can use [KoboldCPP](https://github.com/LostRuins/koboldcpp), which allows you to run quantized GGUF models locally.
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