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README.md
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---
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base_model:
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- v000000/L3.1-8B-RP-Test-003-Task_Arithmetic
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- v000000/L3.1-Niitorm-8B-t0.0001
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- Sao10K/L3.1-8B-Niitama-v1.1
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- arcee-ai/Llama-3.1-SuperNova-Lite
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- akjindal53244/Llama-3.1-Storm-8B
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- arcee-ai/Llama-Spark
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- v000000/L3.1-8B-RP-Test-002-Task_Arithmetic
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- grimjim/Llama-3-Instruct-abliteration-LoRA-8B
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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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- llama
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---
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[](https://hf.co/QuantFactory)
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# QuantFactory/L3.1-Storniitova-8B-GGUF
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This is quantized version of [v000000/L3.1-Storniitova-8B](https://huggingface.co/v000000/L3.1-Storniitova-8B) created using llama.cpp
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# Original Model Card
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# Llama-3.1-Storniitova-8B
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Storniitova-8B is a RP/Instruct model built on the foundation of Llama-3.1-SuperNova-Lite, which is distilled from the 405B parameter variant of Llama-3.1
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By only changing the vector tasks, I attempt to retain the full 405B distillation while learning roleplaying capabilties.
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# (GGUF) mradermacher quants:
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* [GGUFs](https://huggingface.co/mradermacher/L3.1-Storniitova-8B-GGUF)
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* [GGUFs imatrix](https://huggingface.co/mradermacher/L3.1-Storniitova-8B-i1-GGUF)
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-----------------------------------------------------------------------------------------------------------
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# merge
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This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit) and other proprietary tools.
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## Merge Details
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### Merge Method
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This model was merged using the <b>SLERP, Task_Arithmetic and NEARSWAP</b> merge method.
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### Models Merged
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The following models were included in the merge:
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* [v000000/L3.1-Niitorm-8B-t0.0001](https://huggingface.co/v000000/L3.1-Niitorm-8B-t0.0001)
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* [akjindal53244/Llama-3.1-Storm-8B](https://huggingface.co/akjindal53244/Llama-3.1-Storm-8B)
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* [arcee-ai/Llama-Spark](https://huggingface.co/arcee-ai/Llama-Spark)
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* [arcee-ai/Llama-3.1-SuperNova-Lite](https://huggingface.co/arcee-ai/Llama-3.1-SuperNova-Lite)
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* [v000000/L3.1-8B-RP-Test-003-Task_Arithmetic](https://huggingface.co/v000000/L3.1-8B-RP-Test-003-Task_Arithmetic)
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* [Sao10K/L3.1-8B-Niitama-v1.1](https://huggingface.co/Sao10K/L3.1-8B-Niitama-v1.1) + [grimjim/Llama-3-Instruct-abliteration-LoRA-8B](https://huggingface.co/grimjim/Llama-3-Instruct-abliteration-LoRA-8B)
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* [v000000/L3.1-8B-RP-Test-002-Task_Arithmetic](https://huggingface.co/v000000/L3.1-8B-RP-Test-002-Task_Arithmetic) + [grimjim/Llama-3-Instruct-abliteration-LoRA-8B](https://huggingface.co/grimjim/Llama-3-Instruct-abliteration-LoRA-8B)
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### Recipe
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The following YAML configuration was used to produce this model:
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```yaml
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#Step1 - Add smarts to Niitama with alchemonaut's algorithm.
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slices:
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- sources:
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- model: Sao10K/L3.1-8B-Niitama-v1.1+grimjim/Llama-3-Instruct-abliteration-LoRA-8B
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layer_range: [0, 32]
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- model: akjindal53244/Llama-3.1-Storm-8B
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layer_range: [0, 32]
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merge_method: nearswap
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base_model: Sao10K/L3.1-8B-Niitama-v1.1+grimjim/Llama-3-Instruct-abliteration-LoRA-8B
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parameters:
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t:
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- value: 0.0001
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dtype: bfloat16
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out_type: float16
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#Step 2 - Learn vectors onto Supernova 0.4(Niitorm)
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models:
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- model: arcee-ai/Llama-3.1-SuperNova-Lite
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parameters:
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weight: 1.0
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- model: v000000/L3.1-Niitorm-8B-t0.0001
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parameters:
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weight: 0.4
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merge_method: task_arithmetic
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base_model: arcee-ai/Llama-3.1-SuperNova-Lite
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parameters:
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normalize: false
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dtype: float16
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#Step 3 - Fully learn vectors onto Supernova 1.25(Niitorm)
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models:
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- model: arcee-ai/Llama-3.1-SuperNova-Lite
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parameters:
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weight: 0.0
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- model: v000000/L3.1-Niitorm-8B-t0.0001
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parameters:
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weight: 1.25
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merge_method: task_arithmetic
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base_model: arcee-ai/Llama-3.1-SuperNova-Lite
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parameters:
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normalize: false
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dtype: float16
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#Step 4 - Merge checkpoints and keep output/input Supernova heavy
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#Merge with a triangular slerp from sophosympatheia.
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models:
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- model: v000000/L3.1-8B-RP-Test-003-Task_Arithmetic
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merge_method: slerp
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base_model: v000000/L3.1-8B-RP-Test-002-Task_Arithmetic+grimjim/Llama-3-Instruct-abliteration-LoRA-8B
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# This model needed some abliteration^
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parameters:
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t:
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- value: [0, 0, 0.3, 0.4, 0.5, 0.6, 0.5, 0.4, 0.3, 0, 0]
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dtype: float16
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```
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*SLERP distribution* used to smoothly blend the mostly Supernova base with the roleplay vectors:
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