Name	Quant method	Size
This_is_fine_7B.Q2_K.gguf	Q2_K	2.53GB
This_is_fine_7B.IQ3_XS.gguf	IQ3_XS	2.81GB
This_is_fine_7B.IQ3_S.gguf	IQ3_S	2.96GB
This_is_fine_7B.Q3_K_S.gguf	Q3_K_S	2.95GB
This_is_fine_7B.IQ3_M.gguf	IQ3_M	3.06GB
This_is_fine_7B.Q3_K.gguf	Q3_K	3.28GB
This_is_fine_7B.Q3_K_M.gguf	Q3_K_M	3.28GB
This_is_fine_7B.Q3_K_L.gguf	Q3_K_L	3.56GB
This_is_fine_7B.IQ4_XS.gguf	IQ4_XS	3.67GB
This_is_fine_7B.Q4_0.gguf	Q4_0	3.83GB
This_is_fine_7B.IQ4_NL.gguf	IQ4_NL	3.87GB
This_is_fine_7B.Q4_K_S.gguf	Q4_K_S	3.86GB
This_is_fine_7B.Q4_K.gguf	Q4_K	4.07GB
This_is_fine_7B.Q4_K_M.gguf	Q4_K_M	4.07GB
This_is_fine_7B.Q4_1.gguf	Q4_1	4.24GB
This_is_fine_7B.Q5_0.gguf	Q5_0	4.65GB
This_is_fine_7B.Q5_K_S.gguf	Q5_K_S	4.65GB
This_is_fine_7B.Q5_K.gguf	Q5_K	4.78GB
This_is_fine_7B.Q5_K_M.gguf	Q5_K_M	4.78GB
This_is_fine_7B.Q5_1.gguf	Q5_1	5.07GB
This_is_fine_7B.Q6_K.gguf	Q6_K	5.53GB
This_is_fine_7B.Q8_0.gguf	Q8_0	7.17GB

Original model description:

license: other library_name: transformers tags:

mergekit
merge base_model:
jeiku/NarrativeNexus_7B
mlabonne/AlphaMonarch-7B
CultriX/NeuralTrix-bf16
jeiku/Cookie_7B
jeiku/Luna_7B model-index:
name: This_is_fine_7B results:
- task: type: text-generation name: Text Generation dataset: name: AI2 Reasoning Challenge (25-Shot) type: ai2_arc config: ARC-Challenge split: test args: num_few_shot: 25 metrics:
  - type: acc_norm value: 70.31 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ChaoticNeutrals/This_is_fine_7B name: Open LLM Leaderboard
- task: type: text-generation name: Text Generation dataset: name: HellaSwag (10-Shot) type: hellaswag split: validation args: num_few_shot: 10 metrics:
  - type: acc_norm value: 87.28 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ChaoticNeutrals/This_is_fine_7B name: Open LLM Leaderboard
- task: type: text-generation name: Text Generation dataset: name: MMLU (5-Shot) type: cais/mmlu config: all split: test args: num_few_shot: 5 metrics:
  - type: acc value: 64.51 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ChaoticNeutrals/This_is_fine_7B name: Open LLM Leaderboard
- task: type: text-generation name: Text Generation dataset: name: TruthfulQA (0-shot) type: truthful_qa config: multiple_choice split: validation args: num_few_shot: 0 metrics:
  - type: mc2 value: 65.79 source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ChaoticNeutrals/This_is_fine_7B name: Open LLM Leaderboard
- task: type: text-generation name: Text Generation dataset: name: Winogrande (5-shot) type: winogrande config: winogrande_xl split: validation args: num_few_shot: 5 metrics:
  - type: acc value: 81.61 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ChaoticNeutrals/This_is_fine_7B name: Open LLM Leaderboard
- task: type: text-generation name: Text Generation dataset: name: GSM8k (5-shot) type: gsm8k config: main split: test args: num_few_shot: 5 metrics:
  - type: acc value: 62.77 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ChaoticNeutrals/This_is_fine_7B name: Open LLM Leaderboard

Fine

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

Merge Details

Merge Method

This model was merged using the DARE TIES merge method using mlabonne/AlphaMonarch-7B as a base.

Models Merged

The following models were included in the merge:

Configuration

The following YAML configuration was used to produce this model:

yaml

merge_method: dare_ties
base_model: mlabonne/AlphaMonarch-7B
parameters:
  normalize: true
models:
  - model: jeiku/Luna_7B
    parameters:
      weight: 0.75
  - model: jeiku/Cookie_7B
    parameters:
      weight: 1
  - model: jeiku/NarrativeNexus_7B
    parameters:
      weight: 0.5
  - model: CultriX/NeuralTrix-bf16
    parameters:
      weight: 0.75
  - model: mlabonne/AlphaMonarch-7B
    parameters:
      weight: 1           
dtype: float16

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	72.05
AI2 Reasoning Challenge (25-Shot)	70.31
HellaSwag (10-Shot)	87.28
MMLU (5-Shot)	64.51
TruthfulQA (0-shot)	65.79
Winogrande (5-shot)	81.61
GSM8k (5-shot)	62.77

RichardErkhov/ChaoticNeutrals_-_This_is_fine_7B-gguf