L3.1-Celestial-Stone-2x8B-DPO-GGUF

QuantFactory/L3.1-Celestial-Stone-2x8B-DPO-GGUF

This is quantized version of 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).

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

----> Q6_K

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L3.1-Celestial-Stone-2x8B Finetuned on Nvidia A100.

0.5 Epoch completed of dataset jondurbin/gutenberg-dpo-v0.1 with learning_rate=8e-6

Result seems pretty good. More compliant and verbose, less sloppy and safety aligned.

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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>

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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.

Prompt Template:

<|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|>