L3.1-Siithamo-v0.1-8B

My first foray into Llama 3.1 and just having fun with the merging process. Testing theories and such.

Updated version with higher context here.

Quants

OG Q8 GGUF by me.

Details & Recommended Settings

Unfortunaely, this model still double lines but its not as often. Dramatic as fuck at times. I haven't tested the context limit yet but I'm sure it suffered somehow.

Outputs a lot, pretty chatty like Stheno. Pulls some chaotic creativity from Niitama but its mellowed out with Tamamo. A little cliche writing, but it's almost endearing in a way. Should follow instructs fine? Stunted a little compared to the original model, don't think that's a negative though.

4K Max context even on L3.1 (DAMN U FORMAX)

Rec. Settings:

Template: L3
Temperature: 1.35
Min P: 0.1
Repeat Penalty: 1.05
Repeat Penalty Tokens: 256

Models Merged & Merge Theory

The following models were included in the merge:

• Edgerunners/Lyraea-large-llama-3.1
• Sao10K/L3-8B-Stheno-v3.3-32K
• Sao10K/L3.1-8B-Niitama-v1.1
• Sao10K/L3-8B-Tamamo-v1
• ArliAI/ArliAI-Llama-3-8B-Formax-v1.0

Using Edgerunners Lyraea as the 3.1 base, model stock mereged L3.1 Niitama, Stheno 3.3, and Tamamo a top each other. Then trying to curb L3 tendencies and add some instruct following capabilities, added some Formax in a dare linear merge. At least for updating L3 to L3.1, doing TIES anything results in a 'shittier' model.

Config

models:
    - model: Sao10K/L3.1-8B-Niitama-v1.1
    - model: Sao10K/L3-8B-Stheno-v3.3-32K
    - model: Sao10K/L3-8B-Tamamo-v1
base_model: Edgerunners/Lyraea-large-llama-3.1
parameters:
  normalize: false
  int8_mask: true
merge_method: model_stock
dtype: float32
out_dtype: bfloat16
name: siitamol3.1
---
models: 
  - model: ArliAI/ArliAI-Llama-3-8B-Formax-v1.0
    parameters:
      weight: [0.5, 0.3, 0.2, 0.1]
  - model: siitamol3.1
    parameters:
      weight: [0.5, 0.7, 0.8, 1]
base_model: siitamol3.1
parameters:
  normalize: false
  int8_mask: true
merge_method: dare_linear
dtype: float32
out_dtype: bfloat16