Epiculous/Violet_Twilight-v0.2

Now for something a bit different, Violet_Twilight-v0.2! This model is a SLERP merge of Azure_Dusk-v0.2 and Crimson_Dawn-v0.2!

Quants!

full / exl2 / gguf

Prompting

The v0.2 models are trained on ChatML, the prompting structure goes a little something like this:

<|im_start|>user
Hi there!<|im_end|>
<|im_start|>assistant
Nice to meet you!<|im_end|>
<|im_start|>user
Can I ask a question?<|im_end|>
<|im_start|>assistant

Context and Instruct

The v0.2 models are trained on ChatML, please use that Context and Instruct template.

Current Top Sampler Settings

Smooth Creativity: Credit to Juelsman for researching this one!
Variant Chimera: Credit to Numbra!
Spicy_Temp
Violet_Twilight-Nitral-Special

Merging

The following config was used to merge Azure Dusk and Crimson Dawn

slices:
  - sources:
      - model: Epiculous/Azure_Dusk-v0.2
        layer_range: [0, 40]
      - model: Epiculous/Crimson_Dawn-V0.2
        layer_range: [0, 40]
merge_method: slerp
base_model: Epiculous/Azure_Dusk-v0.2
parameters:
  t:
    - filter: self_attn
      value: [0, 0.5, 0.3, 0.7, 1]
    - filter: mlp
      value: [1, 0.5, 0.7, 0.3, 0]
    - value: 0.5 # fallback for rest of tensors
dtype: bfloat16

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	18.53
IFEval (0-Shot)	45.32
BBH (3-Shot)	23.94
MATH Lvl 5 (4-Shot)	2.72
GPQA (0-shot)	2.13
MuSR (0-shot)	13.61
MMLU-PRO (5-shot)	23.45

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	18.53
IFEval (0-Shot)	45.32
BBH (3-Shot)	23.94
MATH Lvl 5 (4-Shot)	2.72
GPQA (0-shot)	2.13
MuSR (0-shot)	13.61
MMLU-PRO (5-shot)	23.45