--- base_model: - v000000/L3.1-8B-RP-Test-003-Task_Arithmetic - v000000/L3.1-Niitorm-8B-t0.0001 - Sao10K/L3.1-8B-Niitama-v1.1 - arcee-ai/Llama-3.1-SuperNova-Lite - akjindal53244/Llama-3.1-Storm-8B - arcee-ai/Llama-Spark - v000000/L3.1-8B-RP-Test-002-Task_Arithmetic - grimjim/Llama-3-Instruct-abliteration-LoRA-8B library_name: transformers tags: - mergekit - merge - llama --- [![QuantFactory Banner](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeiuCm7c8lEwEJuRey9kiVZsRn2W-b4pWlu3-X534V3YmVuVc2ZL-NXg2RkzSOOS2JXGHutDuyyNAUtdJI65jGTo8jT9Y99tMi4H4MqL44Uc5QKG77B0d6-JfIkZHFaUA71-RtjyYZWVIhqsNZcx8-OMaA?key=xt3VSDoCbmTY7o-cwwOFwQ)](https://hf.co/QuantFactory) # QuantFactory/L3.1-Storniitova-8B-GGUF This is quantized version of [v000000/L3.1-Storniitova-8B](https://huggingface.co/v000000/L3.1-Storniitova-8B) created using llama.cpp # Original Model Card # Llama-3.1-Storniitova-8B 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 By only changing the vector tasks, I attempt to retain the full 405B distillation while learning roleplaying capabilties. # (GGUF) mradermacher quants: * [GGUFs](https://huggingface.co/mradermacher/L3.1-Storniitova-8B-GGUF) * [GGUFs imatrix](https://huggingface.co/mradermacher/L3.1-Storniitova-8B-i1-GGUF) ----------------------------------------------------------------------------------------------------------- # merge This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit) and other proprietary tools. ## Merge Details ### Merge Method This model was merged using the SLERP, Task_Arithmetic and NEARSWAP merge method. ### Models Merged The following models were included in the merge: * [v000000/L3.1-Niitorm-8B-t0.0001](https://huggingface.co/v000000/L3.1-Niitorm-8B-t0.0001) * [akjindal53244/Llama-3.1-Storm-8B](https://huggingface.co/akjindal53244/Llama-3.1-Storm-8B) * [arcee-ai/Llama-Spark](https://huggingface.co/arcee-ai/Llama-Spark) * [arcee-ai/Llama-3.1-SuperNova-Lite](https://huggingface.co/arcee-ai/Llama-3.1-SuperNova-Lite) * [v000000/L3.1-8B-RP-Test-003-Task_Arithmetic](https://huggingface.co/v000000/L3.1-8B-RP-Test-003-Task_Arithmetic) * [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) * [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) ### Recipe The following YAML configuration was used to produce this model: ```yaml #Step1 - Add smarts to Niitama with alchemonaut's algorithm. slices: - sources: - model: Sao10K/L3.1-8B-Niitama-v1.1+grimjim/Llama-3-Instruct-abliteration-LoRA-8B layer_range: [0, 32] - model: akjindal53244/Llama-3.1-Storm-8B layer_range: [0, 32] merge_method: nearswap base_model: Sao10K/L3.1-8B-Niitama-v1.1+grimjim/Llama-3-Instruct-abliteration-LoRA-8B parameters: t: - value: 0.0001 dtype: bfloat16 out_type: float16 #Step 2 - Learn vectors onto Supernova 0.4(Niitorm) models: - model: arcee-ai/Llama-3.1-SuperNova-Lite parameters: weight: 1.0 - model: v000000/L3.1-Niitorm-8B-t0.0001 parameters: weight: 0.4 merge_method: task_arithmetic base_model: arcee-ai/Llama-3.1-SuperNova-Lite parameters: normalize: false dtype: float16 #Step 3 - Fully learn vectors onto Supernova 1.25(Niitorm) models: - model: arcee-ai/Llama-3.1-SuperNova-Lite parameters: weight: 0.0 - model: v000000/L3.1-Niitorm-8B-t0.0001 parameters: weight: 1.25 merge_method: task_arithmetic base_model: arcee-ai/Llama-3.1-SuperNova-Lite parameters: normalize: false dtype: float16 #Step 4 - Merge checkpoints and keep output/input Supernova heavy #Merge with a triangular slerp from sophosympatheia. models: - model: v000000/L3.1-8B-RP-Test-003-Task_Arithmetic merge_method: slerp base_model: v000000/L3.1-8B-RP-Test-002-Task_Arithmetic+grimjim/Llama-3-Instruct-abliteration-LoRA-8B # This model needed some abliteration^ parameters: t: - value: [0, 0, 0.3, 0.4, 0.5, 0.6, 0.5, 0.4, 0.3, 0, 0] dtype: float16 ``` *SLERP distribution* used to smoothly blend the mostly Supernova base with the roleplay vectors: ![image/png](https://cdn-uploads.huggingface.co/production/uploads/64f74b6e6389380c77562762/GP2LMRvMkhVJwNDSEC4oU.png)