v000000/SwallowMaid-8B-L3-SPPO-abliterated

General Instruct, RP, Q&A and Storywriting.

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SwallowMaid-8B-Llama-3-SPPO-abliterated

"Llama-3-Instruct-8B-SPPO-Iter3" fully uncensored with 35% RP-Mix infused vector direction to gain some roleplay capabilities and prose while attempting to preserve the qualities of Meta's Llama-3-Instruct finetune.

Thank you mradermacher for the quants!

• GGUFs
• GGUFs imatrix

Quants

• GGUF Q8_0

merge

This is a merge of pre-trained language models created using mergekit.

Merge Details

Merge Method

This model was merged using a multi-step merge method.

Models Merged

The following models were included in the merge:

• grimjim/Llama-3-Instruct-abliteration-LoRA-8B
• UCLA-AGI/Llama-3-Instruct-8B-SPPO-Iter3
• NeverSleep/Llama-3-Lumimaid-8B-v0.1-OAS
• maldv/llama-3-fantasy-writer-8b
• tokyotech-llm/Llama-3-Swallow-8B-v0.1
• Nitral-AI/Hathor_Respawn-L3-8B-v0.8

Configuration

The following YAML configuration was used to produce this model:

# Part 3, Apply abliteration (SwallowMaid-8B)
models:
  - model: sppo-rpmix-part2+grimjim/Llama-3-Instruct-abliteration-LoRA-8B
    parameters:
      weight: 1.0
merge_method: linear
dtype: float32

# Part 2, infuse 35% swallow+rpmix to SPPO-Iter3 (sppo-rpmix-part2)
models:
  - model: UCLA-AGI/Llama-3-Instruct-8B-SPPO-Iter3
    parameters:
      weight: 1.0
  - model: rpmix-part1
    parameters:
      weight: 0.35
merge_method: task_arithmetic
base_model: UCLA-AGI/Llama-3-Instruct-8B-SPPO-Iter3
parameters:
    normalize: false
dtype: float32

# Part 1, linear merge rpmix (rpmix-part1)
models:
  - model: Nitral-AI/Hathor_Respawn-L3-8B-v0.8
    parameters:
      weight: 0.6
  - model: maldv/llama-3-fantasy-writer-8b
    parameters:
      weight: 0.1
  - model: NeverSleep/Llama-3-Lumimaid-8B-v0.1-OAS
    parameters:
      weight: 0.4
  - model: tokyotech-llm/Llama-3-Swallow-8B-v0.1
    parameters:
      weight: 0.15
merge_method: linear
dtype: float32

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|>