60 lines
1.6 KiB
Markdown
60 lines
1.6 KiB
Markdown
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---
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base_model:
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- JoaoReiz/Llama3.2_1B_HAREM
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library_name: transformers
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tags:
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- mergekit
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- merge
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---
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# Harem 3.2 1B
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This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
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## Merge Details
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### Merge Method
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This model was merged using the [SLERP](https://en.wikipedia.org/wiki/Slerp) merge method.
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### Models Merged
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The following models were included in the merge:
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* [JoaoReiz/Llama3.2_1B_HAREM](https://huggingface.co/JoaoReiz/Llama3.2_1B_HAREM)
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### Configuration
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The following YAML configuration was used to produce this model:
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```yaml
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models:
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- model: JoaoReiz/Llama3.2_1B_HAREM # Experimental viral strain neural imprint
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- model: JoaoReiz/Llama3.2_1B_HAREM # Baseline cognitive template, "safe mode"
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merge_method: slerp # Spherical Linear Interpolation to preserve extreme viral traits smoothly
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base_model: JoaoReiz/Llama3.2_1B_HAREM # Anchor model for stable latent space
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dtype: bfloat16 # Memory-efficient precision, minimal loss in viral feature fidelity
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parameters:
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# Interpolation ratios: from base model (0.0) to near-complete T-Virus domination (0.95)
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# Higher t-values correspond to reduced censorship and increased viral characteristics
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t: [0.0, 0.25, 0.5, 0.75, 0.95]
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# Notes:
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# - t=0.0 -> Pure Prototype-Virus-ENFORCE, fully stable, heavily censored
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# - t=0.25 -> Slight viral traits, minimal influence on prompt handling
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# - t=0.5 -> Balanced merge, moderate reduction in censorship
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# - t=0.75 -> Strong T-Virus traits, significantly less censoring
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# - t=0.95 -> Near-total viral influence, maximum expressive freedom, minimal autoprotection
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```
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