---
base_model:
- nothingiisreal/L3.1-8B-Celeste-V1.5
- Sao10K/Llama-3.1-8B-Stheno-v3.4
- Sao10K/L3.1-8B-Niitama-v1.1
- arcee-ai/Llama-3.1-SuperNova-Lite
- akjindal53244/Llama-3.1-Storm-8B
- arcee-ai/Llama-Spark
- grimjim/Llama-3-Instruct-abliteration-LoRA-8B
- crestf411/sunfall-peft
- v000000/L3.1-Celestial-Stone-2x8B
library_name: transformers
tags:
- merge
- llama
- mixtral
- dpo
---
> [!WARNING]
> **Sampler:**
> Likes a low temperature due to the MoE architecture. I use 0.3 personally.
# Llama-3.1-Celestial-Stone-2x8B-DPO (BF16)
* *DPO Trained, Mixture of Experts (14B).*
![image/png](https://cdn-uploads.huggingface.co/production/uploads/64f74b6e6389380c77562762/lyRa7z5maTqAaa43sxC2J.png)
* Direct Preference Optimization run
* *llama.cpp*
# Thanks QuantFactory for the quants:
* [GGUF static](https://huggingface.co/QuantFactory/L3.1-Celestial-Stone-2x8B-DPO-GGUF)
# Thanks Triangle104 for the quants:
* [Q8_0](https://huggingface.co/Triangle104/L3.1-Celestial-Stone-2x8B-DPO-Q8_0-GGUF)
* [Q6_K](https://huggingface.co/Triangle104/L3.1-Celestial-Stone-2x8B-DPO-Q6_K-GGUF)
* [Q5_K_M](https://huggingface.co/Triangle104/L3.1-Celestial-Stone-2x8B-DPO-Q5_K_M-GGUF)
* [Q5_K_S](https://huggingface.co/Triangle104/L3.1-Celestial-Stone-2x8B-DPO-Q5_K_S-GGUF)
* [Q4_K_M](https://huggingface.co/Triangle104/L3.1-Celestial-Stone-2x8B-DPO-Q4_K_M-GGUF)
* [Q4_K_S](https://huggingface.co/Triangle104/L3.1-Celestial-Stone-2x8B-DPO-Q4_K_S-GGUF)
---------------------------------------------------------------------------------
[L3.1-Celestial-Stone-2x8B](https://huggingface.co/v000000/L3.1-Celestial-Stone-2x8B) Finetuned on Nvidia A100.
0.5 Epoch completed of dataset [jondurbin/gutenberg-dpo-v0.1](https://huggingface.co/datasets/jondurbin/gutenberg-dpo-v0.1) with learning_rate=8e-6
Result seems pretty good. More compliant and verbose, less sloppy and safety aligned.
------------------------------------------------------------------------------
*The first expert* is Instruct 405B distillation/RP vector merge (Supernova-Lite, Niitama1.1, Storm)
*The second expert* is ERP/Reddit data merge (Celeste1.5, Stheno3.4, Storm)
-------------------------------------------------------------------------------
*The base model* is Sao10k/L3.1-Stheno-3.4 with the Sunfall LoRa 0.6.1 to make it understand SillyTavern prompts and storywriting better.
-------------------------------------------------------------------------------
*Resultant merge finetuned* on [jondurbin/gutenberg-dpo-v0.1](https://huggingface.co/datasets/jondurbin/gutenberg-dpo-v0.1).
# Prompt Template:
```bash
<|begin_of_text|><|start_header_id|>system<|end_header_id|>
{system_prompt}<|eot_id|><|start_header_id|>user<|end_header_id|>
{input}<|eot_id|><|start_header_id|>assistant<|end_header_id|>
{output}<|eot_id|>
```