Dedicated Endpoints

Run this model inference on single tenant GPU with unmatched speed and reliability at scale.

Learn more
Container

Run this model inference with full control and performance in your environment.

Learn more

Get help setting up a custom Dedicated Endpoints.

Talk with our engineer to get a quote for reserved GPU instances with discounts.

README

🧬 Merge Overview

LunaMaid-12B was produced through a two-stage multi-model merge using MergeKit.
Each stage fuses models with complementary linguistic and stylistic traits to create a cohesive, emotionally nuanced personality.

🩵 Stage 1 — Slerp Merge (Intermediate Model First)

yaml

name: First
base_model: Vortex5/Vermilion-Sage-12B
models:
- model: yamatazen/NeonMaid-12B-v2
merge_method: slerp
dtype: bfloat16
parameters:
normalize: true
t: [0.25, 0.35, 0.45, 0.55, 0.65, 0.75, 0.6, 0.5, 0.6, 0.6]

🌑 Merge Method — Karcher Mean Merge (Final Model)

yaml

dtype: bfloat16
merge_method: karcher
modules:
default:
slices:
- sources:
- layer_range: [0, 40]
model: ./intermediates/First
- layer_range: [0, 40]
model: Vortex5/Moonlit-Shadow-12B
parameters:
max_iter: 9999
tol: 1e-9

Models Merged

The following models were included in the merge:

Model provider

Vortex5

Vortex5

Model tree

Base

Vortex5/Moonlit-Shadow-12B

Base

yamatazen/NeonMaid-12B-v2

Base

Vortex5/Vermilion-Sage-12B

Merged

this model

Modalities

Input

Text

Output

Text

Pricing

Dedicated Endpoints

View details

Supported Functionality

Model APIs

Dedicated Endpoints

Container

More information

Explore FriendliAI today