Konstanta-Alpha-V2-7B/README.md

language, license, library_name, tags, base_model, model-index

language	license	library_name	tags	base_model	model-index
en	apache-2.0	transformers	mergekit merge mistralai/Mistral-7B-v0.1 SanjiWatsuki/Kunoichi-DPO-v2-7B maywell/PiVoT-0.1-Evil-a mlabonne/ArchBeagle-7B LakoMoor/Silicon-Alice-7B roleplay rp not-for-all-audiences	mistralai/Mistral-7B-v0.1 SanjiWatsuki/Kunoichi-DPO-v2-7B maywell/PiVoT-0.1-Evil-a mlabonne/ArchBeagle-7B LakoMoor/Silicon-Alice-7B	name results Konstanta-Alpha-V2-7B task dataset metrics source type name text-generation Text Generation name type config split args AI2 Reasoning Challenge (25-Shot) ai2_arc ARC-Challenge test num_few_shot 25 type value name acc_norm 69.62 normalized accuracy url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Inv/Konstanta-Alpha-V2-7B Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type split args HellaSwag (10-Shot) hellaswag validation num_few_shot 10 type value name acc_norm 87.14 normalized accuracy url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Inv/Konstanta-Alpha-V2-7B Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type config split args MMLU (5-Shot) cais/mmlu all test num_few_shot 5 type value name acc 65.11 accuracy url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Inv/Konstanta-Alpha-V2-7B Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type config split args TruthfulQA (0-shot) truthful_qa multiple_choice validation num_few_shot 0 type value mc2 61.08 url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Inv/Konstanta-Alpha-V2-7B Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type config split args Winogrande (5-shot) winogrande winogrande_xl validation num_few_shot 5 type value name acc 81.22 accuracy url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Inv/Konstanta-Alpha-V2-7B Open LLM Leaderboard task dataset metrics source type name text-generation Text Generation name type config split args GSM8k (5-shot) gsm8k main test num_few_shot 5 type value name acc 69.9 accuracy url name https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Inv/Konstanta-Alpha-V2-7B Open LLM Leaderboard

Konstanta-Alpha-V2-7B

This is a merge of pre-trained language models created using mergekit.

Merge Details

Merge Method

This model was merged using the DARE TIES to merge Kunoichi with PiVoT Evil and to merge ArchBeagle with Silicon Alice, and then merge the resulting 2 models with the gradient SLERP merge method. ChatML seems to work the best.

Models Merged

The following models were included in the merge:

• SanjiWatsuki/Kunoichi-DPO-v2-7B
• maywell/PiVoT-0.1-Evil-a
• mlabonne/ArchBeagle-7B
• LakoMoor/Silicon-Alice-7B

Configuration

The following YAML configuration was used to produce this model (to reproduce use mergekit-mega command):

base_model: mistralai/Mistral-7B-v0.1
dtype: float16
merge_method: dare_ties
parameters:
  int8_mask: true
slices:
- sources:
  - layer_range: [0, 32]
    model: mistralai/Mistral-7B-v0.1
  - layer_range: [0, 32]
    model: : SanjiWatsuki/Kunoichi-DPO-v2-7B
    parameters:
      density: 0.8
      weight: 0.5
  - layer_range: [0, 32]
    model: : maywell/PiVoT-0.1-Evil-a
    parameters:
      density: 0.3
      weight: 0.15
name: first-step
---
base_model: mistralai/Mistral-7B-v0.1
dtype: float16
merge_method: dare_ties
parameters:
  int8_mask: true
slices:
- sources:
  - layer_range: [0, 32]
    model: mistralai/Mistral-7B-v0.1
  - layer_range: [0, 32]
    model: mlabonne/ArchBeagle-7B
    parameters:
      density: 0.8
      weight: 0.75
  - layer_range: [0, 32]
    model: LakoMoor/Silicon-Alice-7B
    parameters:
      density: 0.6
      weight: 0.30
name: second-step
---
models:
   - model: first-step
   - model: second-step
merge_method: slerp
base_model: first-step
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
  int8_mask: true
  normalize: true
dtype: float16

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	72.35
AI2 Reasoning Challenge (25-Shot)	69.62
HellaSwag (10-Shot)	87.14
MMLU (5-Shot)	65.11
TruthfulQA (0-shot)	61.08
Winogrande (5-shot)	81.22
GSM8k (5-shot)	69.90