README.md

---

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

---

[![QuantFactory Banner](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeiuCm7c8lEwEJuRey9kiVZsRn2W-b4pWlu3-X534V3YmVuVc2ZL-NXg2RkzSOOS2JXGHutDuyyNAUtdJI65jGTo8jT9Y99tMi4H4MqL44Uc5QKG77B0d6-JfIkZHFaUA71-RtjyYZWVIhqsNZcx8-OMaA?key=xt3VSDoCbmTY7o-cwwOFwQ)](https://hf.co/QuantFactory)


# QuantFactory/L3.1-Celestial-Stone-2x8B-DPO-GGUF
This is quantized version of [v000000/L3.1-Celestial-Stone-2x8B-DPO](https://huggingface.co/v000000/L3.1-Celestial-Stone-2x8B-DPO) created using llama.cpp

# Original Model Card


> [!WARNING]
> **Sampler:**<br>
> 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)

* <b>Direct Preference Optimization run</b>

----> [Q6_K](https://huggingface.co/v000000/L3.1-Celestial-Stone-2x8B-DPO-Q6_K-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 <b>(Supernova-Lite, Niitama1.1, Storm)</b>

*The second expert* is ERP/Reddit data merge <b>(Celeste1.5, Stheno3.4, Storm)</b>

-------------------------------------------------------------------------------

*The base model* is <b>Sao10k/L3.1-Stheno-3.4</b> with the <b>Sunfall LoRa 0.6.1</b> to make it understand SillyTavern prompts and storywriting better.

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*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|>

```