QuantFactory/Violet_Twilight-v0.2-GGUF

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/nopmclaudewriting_fixed
• —anthracite-org/kaloopusmisc240827 pipelinetag: 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: numfewshot: 0 metrics:
• —type: instlevelstrictacc and promptlevelstrictacc value: 45.32 name: strict accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/openllmleaderboard?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: numfewshot: 3 metrics:
• —type: accnorm value: 23.94 name: normalized accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/openllmleaderboard?query=Epiculous/VioletTwilight-v0.2 name: Open LLM Leaderboard
• —task: type: text-generation name: Text Generation dataset: name: MATH Lvl 5 (4-Shot) type: hendrycks/competitionmath args: numfew_shot: 4 metrics:
• —type: exactmatch value: 2.72 name: exact match source: url: https://huggingface.co/spaces/open-llm-leaderboard/openllmleaderboard?query=Epiculous/VioletTwilight-v0.2 name: Open LLM Leaderboard
• —task: type: text-generation name: Text Generation dataset: name: GPQA (0-shot) type: Idavidrein/gpqa args: numfewshot: 0 metrics:
• —type: accnorm value: 2.13 name: accnorm source: url: https://huggingface.co/spaces/open-llm-leaderboard/openllmleaderboard?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: numfewshot: 0 metrics:
• —type: accnorm value: 13.61 name: accnorm source: url: https://huggingface.co/spaces/open-llm-leaderboard/openllmleaderboard?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: numfewshot: 5 metrics:
• —type: acc value: 23.45 name: accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/openllmleaderboard?query=Epiculous/Violet_Twilight-v0.2 name: Open LLM Leaderboard


QuantFactory/Violet_Twilight-v0.2-GGUF

This is quantized version of Epiculous/Violet_Twilight-v0.2 created using llama.cpp

Original Model Card

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

Quants!

<strong>full</strong> / 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

Spicy_Temp <br/> Violet_Twilight-Nitral-Special <br/>

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