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---
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license: gemma
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---
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[![QuantFactory Banner](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeiuCm7c8lEwEJuRey9kiVZsRn2W-b4pWlu3-X534V3YmVuVc2ZL-NXg2RkzSOOS2JXGHutDuyyNAUtdJI65jGTo8jT9Y99tMi4H4MqL44Uc5QKG77B0d6-JfIkZHFaUA71-RtjyYZWVIhqsNZcx8-OMaA?key=xt3VSDoCbmTY7o-cwwOFwQ)](https://hf.co/QuantFactory)
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# QuantFactory/Gemma-2-2B-ArliAI-RPMax-v1.1-GGUF
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This is quantized version of [ArliAI/Gemma-2-2B-ArliAI-RPMax-v1.1](https://huggingface.co/ArliAI/Gemma-2-2B-ArliAI-RPMax-v1.1) created using llama.cpp
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# Original Model Card
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# Gemma-2-2B-ArliAI-RPMax-v1.1
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=====================================
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## RPMax Series Overview
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| [2B](https://huggingface.co/ArliAI/Gemma-2-2B-ArliAI-RPMax-v1.1) |
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[3.8B](https://huggingface.co/ArliAI/Phi-3.5-mini-3.8B-ArliAI-RPMax-v1.1) |
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[8B](https://huggingface.co/ArliAI/Llama-3.1-8B-ArliAI-RPMax-v1.1) |
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[9B](https://huggingface.co/ArliAI/Gemma-2-9B-ArliAI-RPMax-v1.1) |
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[12B](https://huggingface.co/ArliAI/Mistral-Nemo-12B-ArliAI-RPMax-v1.1) |
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[20B](https://huggingface.co/ArliAI/InternLM_2_5-20B-ArliAI-RPMax-v1.1) |
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[70B](https://huggingface.co/ArliAI/Llama-3.1-70B-ArliAI-RPMax-v1.1) |
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RPMax is a series of models that are trained on a diverse set of curated creative writing and RP datasets with a focus on variety and deduplication. This model is designed to be highly creative and non-repetitive by making sure no two entries in the dataset have repeated characters or situations, which makes sure the model does not latch on to a certain personality and be capable of understanding and acting appropriately to any characters or situations.
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Early tests by users mentioned that these models does not feel like any other RP models, having a different style and generally doesn't feel in-bred.
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You can access the models at https://arliai.com and ask questions at https://www.reddit.com/r/ArliAI/
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We also have a models ranking page at https://www.arliai.com/models-ranking
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Ask questions in our new Discord Server! https://discord.gg/aDVx6FZN
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## Model Description
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Gemma-2-2B-ArliAI-RPMax-v1.1 is a variant based on gemma-22b-it.
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### Training Details
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* **Sequence Length**: 4096
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* **Training Duration**: Approximately less than 1 day on 2x3090Ti
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* **Epochs**: 1 epoch training for minimized repetition sickness
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* **QLORA**: 64-rank 128-alpha, resulting in ~2% trainable weights
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* **Learning Rate**: 0.00001
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* **Gradient accumulation**: Very low 32 for better learning.
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## Quantization
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The model is available in quantized formats:
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* **FP16**: https://huggingface.co/ArliAI/Gemma-2-2B-ArliAI-RPMax-v1.1
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* **GPTQ_Q4**: https://huggingface.co/ArliAI/Gemma-2-2B-ArliAI-RPMax-v1.1-GPTQ_Q4
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* **GPTQ_Q8**: https://huggingface.co/ArliAI/Gemma-2-2B-ArliAI-RPMax-v1.1-GPTQ_Q8
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* **GGUF**: https://huggingface.co/ArliAI/Gemma-2-2B-ArliAI-RPMax-v1.1-GGUF
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## Suggested Prompt Format
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Gemma Instruct Prompt Format
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Since Gemma does not have system prompts, put the character descriptions in the first turn like on Mistral models.
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It is trained with ```<instructions>``` and ```<end_of_instructions>``` that enclose the system prompt in the first user message.
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```
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<bos><start_of_turn>user
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<instructions>You are a (character description)<end_of_instructions>\n\nHello!<end_of_turn>
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<start_of_turn>model
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```
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