Quantization made by Richard Erkhov.

Sina-Odin-7b-Merge - GGUF

Model creator: https://huggingface.co/Azazelle/
Original model: https://huggingface.co/Azazelle/Sina-Odin-7b-Merge/

Name	Quant method	Size
Sina-Odin-7b-Merge.Q2_K.gguf	Q2_K	2.53GB
Sina-Odin-7b-Merge.IQ3_XS.gguf	IQ3_XS	2.81GB
Sina-Odin-7b-Merge.IQ3_S.gguf	IQ3_S	2.96GB
Sina-Odin-7b-Merge.Q3_K_S.gguf	Q3_K_S	2.95GB
Sina-Odin-7b-Merge.IQ3_M.gguf	IQ3_M	3.06GB
Sina-Odin-7b-Merge.Q3_K.gguf	Q3_K	3.28GB
Sina-Odin-7b-Merge.Q3_K_M.gguf	Q3_K_M	3.28GB
Sina-Odin-7b-Merge.Q3_K_L.gguf	Q3_K_L	3.56GB
Sina-Odin-7b-Merge.IQ4_XS.gguf	IQ4_XS	3.67GB
Sina-Odin-7b-Merge.Q4_0.gguf	Q4_0	3.83GB
Sina-Odin-7b-Merge.IQ4_NL.gguf	IQ4_NL	3.87GB
Sina-Odin-7b-Merge.Q4_K_S.gguf	Q4_K_S	3.86GB
Sina-Odin-7b-Merge.Q4_K.gguf	Q4_K	4.07GB
Sina-Odin-7b-Merge.Q4_K_M.gguf	Q4_K_M	4.07GB
Sina-Odin-7b-Merge.Q4_1.gguf	Q4_1	4.24GB
Sina-Odin-7b-Merge.Q5_0.gguf	Q5_0	4.65GB
Sina-Odin-7b-Merge.Q5_K_S.gguf	Q5_K_S	4.65GB
Sina-Odin-7b-Merge.Q5_K.gguf	Q5_K	4.78GB
Sina-Odin-7b-Merge.Q5_K_M.gguf	Q5_K_M	4.78GB
Sina-Odin-7b-Merge.Q5_1.gguf	Q5_1	5.07GB
Sina-Odin-7b-Merge.Q6_K.gguf	Q6_K	5.53GB
Sina-Odin-7b-Merge.Q8_0.gguf	Q8_0	7.17GB

Original model description:

license: cc-by-4.0 tags: - mistral - merge pipeline_tag: text-generation model-index: - name: Sina-Odin-7b-Merge 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: 52.82 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Azazelle/Sina-Odin-7b-Merge 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: 68.86 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Azazelle/Sina-Odin-7b-Merge 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: 45.54 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Azazelle/Sina-Odin-7b-Merge 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: 39.2 source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Azazelle/Sina-Odin-7b-Merge 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: 72.22 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Azazelle/Sina-Odin-7b-Merge 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: 8.26 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=Azazelle/Sina-Odin-7b-Merge name: Open LLM Leaderboard

Model Card for Sina-Odin-7b-Merge

Part of a series of experimental DARE merges.

.yaml file for mergekit

models:
  - model: Mihaiii/Metis-0.3
    # no parameters necessary for base model
  - model: rishiraj/smol-7b #75
    parameters:
      weight: 0.2
      density: 0.41
  - model: SanjiWatsuki/openchat-3.5-1210-starling-slerp #125
    parameters:
      weight: 0.33
      density: 0.54
  - model: Azazelle/Dumb-Maidlet #200
    parameters:
      weight: 0.53
      density: 0.71
merge_method: dare_ties
base_model: Mihaiii/Metis-0.3
parameters:
  int8_mask: true
dtype: bfloat16

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	47.82
AI2 Reasoning Challenge (25-Shot)	52.82
HellaSwag (10-Shot)	68.86
MMLU (5-Shot)	45.54
TruthfulQA (0-shot)	39.20
Winogrande (5-shot)	72.22
GSM8k (5-shot)	8.26