muzerai/Llama-3.1-8B-Ko-4oDistil-Heresy-DARE-GGUF

Llama-3.1-8B-Ko-4oDistil-Heresy-DARE

Overview

Llama-3.1-8B-Ko-4oDistil-Heresy-DARE is an experimental 8B merged model combining:

• Korean instruction-tuned alignment
• GPT-style response formatting tendencies (via 4o-distilled variant; style-level influence only)
• Reduced refusal behavior relative to strongly safety-aligned variants (experimental observation)

This model merges:

• ➤ Korean Base Model
  https://huggingface.co/sh2orc/Llama-3.1-Korean-8B-Instruct

• ➤ GPT-4o Distilled Heresy Variant
  https://huggingface.co/MuXodious/gpt-4o-distil-Llama-3.1-8B-Instruct-PaperWitch-heresy

The merge was performed using DARE-TIES.

This is a community-driven experimental merge and has not undergone formal benchmarking.
Performance characteristics may vary depending on quantization method, inference settings, and prompt structure.

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Intended Characteristics

This model aims to provide:

• Natural Korean conversational fluency
• Moderately structured, explanation-oriented outputs
• Reduced over-refusal tendencies compared to strictly aligned instruction models
• More flexible text generation due to relaxed alignment constraints

It is particularly suited for:

• Korean conversational assistants
• Creative writing and expressive content
• Brainstorming and exploratory dialogue
• Alignment-shift and merge methodology research

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Known Limitations

• Not optimized for high-precision logical reasoning
• May produce factual inaccuracies in technical, numerical, or specialized domains
• Formatting compliance may vary
• Reduced refusal behavior increases the need for external moderation in deployment scenarios

This model is not recommended for:

• Financial, legal, or safety-critical advisory use
• High-accuracy technical documentation
• Formal mathematical or multi-step logical validation tasks

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Quantized Versions (Recommended)

Format	Use Case
Q4_K_M	Recommended balance between quality and efficiency
Q5_K_M	Higher quality, increased memory usage
Q3_K_M	Lightweight option for constrained environments

Lower-bit quantization may reduce reasoning stability and output consistency.

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ModelFile (ollama)

FROM llama-3.1-8b-ko-4odistil-heresy-dare-Q5_K_M.gguf
TEMPLATE """{{ if .Messages }}
{{- if or .System .Tools }}<|start_header_id|>system<|end_header_id|>
{{- if .System }}

{{ .System }}
{{- end }}
{{- if .Tools }}

You are a helpful assistant with tool calling capabilities. When you receive a tool call response, use the output to format an answer to the original user question.
{{- end }}
{{- end }}<|eot_id|>
{{- range $i, $_ := .Messages }}
{{- $last := eq (len (slice $.Messages $i)) 1 }}
{{- if eq .Role "user" }}<|start_header_id|>user<|end_header_id|>
{{- if and $.Tools $last }}

Given the following functions, please respond with a JSON for a function call with its proper arguments that best answers the given prompt.

Respond in the format {"name": function name, "parameters": dictionary of argument name and its value}. Do not use variables.

{{ $.Tools }}
{{- end }}

{{ .Content }}<|eot_id|>{{ if $last }}<|start_header_id|>assistant<|end_header_id|>

{{ end }}
{{- else if eq .Role "assistant" }}<|start_header_id|>assistant<|end_header_id|>
{{- if .ToolCalls }}

{{- range .ToolCalls }}{"name": "{{ .Function.Name }}", "parameters": {{ .Function.Arguments }}}{{ end }}
{{- else }}

{{ .Content }}{{ if not $last }}<|eot_id|>{{ end }}
{{- end }}
{{- else if eq .Role "tool" }}<|start_header_id|>ipython<|end_header_id|>

{{ .Content }}<|eot_id|>{{ if $last }}<|start_header_id|>assistant<|end_header_id|>

{{ end }}
{{- end }}
{{- end }}
{{- else }}
{{- if .System }}<|start_header_id|>system<|end_header_id|>

{{ .System }}<|eot_id|>{{ end }}{{ if .Prompt }}<|start_header_id|>user<|end_header_id|>

{{ .Prompt }}<|eot_id|>{{ end }}<|start_header_id|>assistant<|end_header_id|>

{{ end }}{{ .Response }}{{ if .Response }}<|eot_id|>{{ end }}"""

PARAMETER stop <|start_header_id|>
PARAMETER stop <|end_header_id|>
PARAMETER stop <|eot_id|>
PARAMETER temperature 0.6

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Important Notes

This model incorporates traits from a reduced-refusal variant. As such:

• It may respond more freely than standard safety-aligned models
• It may require external moderation in production environments
• It is intended primarily for research and experimental use

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Disclaimer

This is a community-merged experimental model and is not officially affiliated with Meta or OpenAI.

Outputs may require review, moderation, and independent verification before real-world application.

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Citations

@misc{dare_ties_merge_2026,
  title  = {DARE-TIES Community Merge Experiment},
  author = {GrooveJ},
  year   = {2026}
}