README.md

---
license: llama3
model-index:
- name: Llama-3.1-8B-ArliAI-RPMax-v1.1
  results:
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: IFEval (0-Shot)
      type: HuggingFaceH4/ifeval
      args:
        num_few_shot: 0
    metrics:
    - type: inst_level_strict_acc and prompt_level_strict_acc
      value: 63.59
      name: strict accuracy
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=ArliAI/Llama-3.1-8B-ArliAI-RPMax-v1.1
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: BBH (3-Shot)
      type: BBH
      args:
        num_few_shot: 3
    metrics:
    - type: acc_norm
      value: 28.79
      name: normalized accuracy
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=ArliAI/Llama-3.1-8B-ArliAI-RPMax-v1.1
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MATH Lvl 5 (4-Shot)
      type: hendrycks/competition_math
      args:
        num_few_shot: 4
    metrics:
    - type: exact_match
      value: 11.33
      name: exact match
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=ArliAI/Llama-3.1-8B-ArliAI-RPMax-v1.1
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: GPQA (0-shot)
      type: Idavidrein/gpqa
      args:
        num_few_shot: 0
    metrics:
    - type: acc_norm
      value: 4.47
      name: acc_norm
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=ArliAI/Llama-3.1-8B-ArliAI-RPMax-v1.1
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MuSR (0-shot)
      type: TAUR-Lab/MuSR
      args:
        num_few_shot: 0
    metrics:
    - type: acc_norm
      value: 5.31
      name: acc_norm
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=ArliAI/Llama-3.1-8B-ArliAI-RPMax-v1.1
      name: Open LLM Leaderboard
  - task:
      type: text-generation
      name: Text Generation
    dataset:
      name: MMLU-PRO (5-shot)
      type: TIGER-Lab/MMLU-Pro
      config: main
      split: test
      args:
        num_few_shot: 5
    metrics:
    - type: acc
      value: 28.35
      name: accuracy
    source:
      url: https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard?query=ArliAI/Llama-3.1-8B-ArliAI-RPMax-v1.1
      name: Open LLM Leaderboard
---

# Llama-3.1-8B-ArliAI-RPMax-v1.1
=====================================

## RPMax Series Overview

| [3.8B](https://huggingface.co./ArliAI/Phi-3.5-mini-3.8B-ArliAI-RPMax-v1.1) | 
[8B](https://huggingface.co./ArliAI/Llama-3.1-8B-ArliAI-RPMax-v1.1) | 
[12B](https://huggingface.co./ArliAI/Mistral-Nemo-12B-ArliAI-RPMax-v1.1) | 
[70B](https://huggingface.co./ArliAI/Llama-3.1-70B-ArliAI-RPMax-v1.1) | 

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.

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.

You can access the model at https://arliai.com and ask questions at https://www.reddit.com/r/ArliAI/

We also have a models ranking page at https://www.arliai.com/models-ranking

Ask questions in our new Discord Server! https://discord.gg/aDVx6FZN

## Model Description

Llama-3.1-8B-ArliAI-RPMax-v1.1 is a variant of the Meta-Llama-3.1-8B model.

v1.1 is just a small fix to not train and save the embeddings layer and small changes to the dataset, since v1.0 had the lm_head unnecessarily trained on accident.

### Training Details

* **Sequence Length**: 8192
* **Training Duration**: Approximately 1 day on 2x3090Ti
* **Epochs**: 1 epoch training for minimized repetition sickness
* **LORA**: 64-rank 128-alpha, resulting in ~2% trainable weights
* **Learning Rate**: 0.00001
* **Gradient accumulation**: Very low 32 for better learning.

## Quantization

The model is available in quantized formats:

We recommend using full weights or GPTQ

* **FP16**: https://huggingface.co./ArliAI/Llama-3.1-8B-ArliAI-RPMax-v1.1
* **GPTQ_Q4**: https://huggingface.co./ArliAI/Llama-3.1-8B-ArliAI-RPMax-v1.1-GPTQ_Q4
* **GPTQ_Q8**: https://huggingface.co./ArliAI/Llama-3.1-8B-ArliAI-RPMax-v1.1-GPTQ_Q8
* **GGUF**: https://huggingface.co./ArliAI/Llama-3.1-8B-ArliAI-RPMax-v1.1-GGUF

## Suggested Prompt Format

Llama 3 Instruct Format

Example:
```
<|begin_of_text|><|start_header_id|>system<|end_header_id|>

You are [character]. You have a personality of [personality description]. [Describe scenario]<|eot_id|><|start_header_id|>user<|end_header_id|>

{{ user_message_1 }}<|eot_id|><|start_header_id|>assistant<|end_header_id|>

{{ model_answer_1 }}<|eot_id|><|start_header_id|>user<|end_header_id|>

{{ user_message_2 }}<|eot_id|><|start_header_id|>assistant<|end_header_id|>
```
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co./spaces/open-llm-leaderboard/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co./datasets/open-llm-leaderboard/details_ArliAI__Llama-3.1-8B-ArliAI-RPMax-v1.1)

|      Metric       |Value|
|-------------------|----:|
|Avg.               |23.64|
|IFEval (0-Shot)    |63.59|
|BBH (3-Shot)       |28.79|
|MATH Lvl 5 (4-Shot)|11.33|
|GPQA (0-shot)      | 4.47|
|MuSR (0-shot)      | 5.31|
|MMLU-PRO (5-shot)  |28.35|