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!
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 |