README.md

---
license: llama3
pipeline_tag: text-generation
base_model: OwenArli/ArliAI-Llama-3-8B-Dolfin-v1.0
---

# QuantFactory/ArliAI-Llama-3-8B-Dolfin-v1.0-GGUF
This is quantized version of [OwenArli/ArliAI-Llama-3-8B-Dolfin-v1.0](https://huggingface.co/OwenArli/ArliAI-Llama-3-8B-Dolfin-v1.0) created using llama.cpp

# Model Description
Based on Meta-Llama-3-8b-Instruct, and is governed by Meta Llama 3 License agreement:
https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct


Base model: https://huggingface.co/failspy/Meta-Llama-3-8B-Instruct-abliterated-v3


SFT fine tune of Meta Llama 3 8B Instruct Abliterated v3 by Failspy using an improved Dolphin and WizardLM dataset intended to remove GPT-isms and make the model follow instructions more exactly while paying attention to details better.

Since it is based on the Abliterated version of Llama 3 8B Instruct it should naturally not refuse to answer in the first place and this fine tuning should make it comply even better. 


Best practices:
  - Be precise and explain what you want the model to do. It has less base "personality" than the OG model but it will act however you tell it to.
  - This model works best with system prompts that tells it that it is the character, instead of telling it to act as a character. 

Training:
- Full 8192 sequence length 
- Training duration is around 2.5 days on an RTX 4090
- 1 epoch training with a massive dataset for minimized repetition sickness.
- Using 4-bit loading and Qlora 64-rank 64-alpha resulting in ~2% trainable weights.


Llama 3 Instruct format:
```
<|begin_of_text|><|start_header_id|>system<|end_header_id|>

{{ system_prompt }}<|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|>
```