language:

• en
• fr
• de
• es
• it
• pt
• ru
• zh
• ja license: apache-2.0 tags:
• merge datasets:
• Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned
• anthracite-org/stheno-filtered-v1.1
• PJMixers/hieunguyenminh_roleplay-deduped-ShareGPT
• Gryphe/Sonnet3.5-Charcard-Roleplay
• Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned
• anthracite-org/kalo-opus-instruct-22k-no-refusal
• anthracite-org/nopm_claude_writing_fixed
• anthracite-org/kalo_opus_misc_240827 pipeline_tag: text-generation model-index:
• name: Violet_Twilight-v0.2 results:
  • task: type: text-generation name: Text Generation dataset: name: IFEval (0-Shot) type: HuggingFaceH4/ifeval args: num_few_shot: 0 metrics:
    • type: inst_level_strict_acc and prompt_level_strict_acc value: 45.32 name: strict accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Epiculous/Violet_Twilight-v0.2 name: Open LLM Leaderboard
  • task: type: text-generation name: Text Generation dataset: name: BBH (3-Shot) type: BBH args: num_few_shot: 3 metrics:
    • type: acc_norm value: 23.94 name: normalized accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Epiculous/Violet_Twilight-v0.2 name: Open LLM Leaderboard
  • task: type: text-generation name: Text Generation dataset: name: MATH Lvl 5 (4-Shot) type: hendrycks/competition_math args: num_few_shot: 4 metrics:
    • type: exact_match value: 2.72 name: exact match source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Epiculous/Violet_Twilight-v0.2 name: Open LLM Leaderboard
  • task: type: text-generation name: Text Generation dataset: name: GPQA (0-shot) type: Idavidrein/gpqa args: num_few_shot: 0 metrics:
    • type: acc_norm value: 2.13 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Epiculous/Violet_Twilight-v0.2 name: Open LLM Leaderboard
  • task: type: text-generation name: Text Generation dataset: name: MuSR (0-shot) type: TAUR-Lab/MuSR args: num_few_shot: 0 metrics:
    • type: acc_norm value: 13.61 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Epiculous/Violet_Twilight-v0.2 name: Open LLM Leaderboard
  • task: type: text-generation name: Text Generation dataset: name: MMLU-PRO (5-shot) type: TIGER-Lab/MMLU-Pro config: main split: test args: num_few_shot: 5 metrics:
    • type: acc value: 23.45 name: accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Epiculous/Violet_Twilight-v0.2 name: Open LLM Leaderboard

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

Open LLM Leaderboard Evaluation Results

Detailed results can be found here