Self-attention layers: Gradual blend from base to creative (0 -> 0.5 -> 0.3 -> 0.7 -> 1)
MLP layers: Inverse blend (1 -> 0.5 -> 0.7 -> 0.3 -> 0)
Default: 50/50 blend

This approach preserves the base model's instruction-following while incorporating the creative writing capabilities of the remnant fine-tune.

Quantizations

Quant	Size	Description
Q4_K_M	4.7 GB	Balanced quality and size (recommended)
Q5_K_M	5.5 GB	Better quality, slightly larger
Q8_0	8.2 GB	Highest quality quantization

Usage

llama.cpp

./llama-cli -m RemnantInstruct-8B-Q4_K_M.gguf -p "Write a story about..." -n 512

Ollama

ollama run anthonym21/remnantinstruct-8b

LM Studio

Download any GGUF file and load it directly in LM Studio.

Merge Configuration

yaml

slices:
  - sources:
      - model: Qwen/Qwen3-8B
        layer_range: [0, 36]
      - model: allura-org/remnant-qwen3-8b
        layer_range: [0, 36]
merge_method: slerp
base_model: Qwen/Qwen3-8B
parameters:
  t:
    - filter: self_attn
      value: [0, 0.5, 0.3, 0.7, 1]
    - filter: mlp
      value: [1, 0.5, 0.7, 0.3, 0]
    - value: 0.5
dtype: bfloat16

License

Apache 2.0 (inherited from Qwen3-8B)

anthonym21/RemnantInstruct-8B-GGUF

RemnantInstruct-8B-GGUF

Model Details