Name	Quant method	Size
Llama-3.1-8B-Ultra-Instruct.Q2_K.gguf	Q2_K	2.96GB
Llama-3.1-8B-Ultra-Instruct.IQ3_XS.gguf	IQ3_XS	3.28GB
Llama-3.1-8B-Ultra-Instruct.IQ3_S.gguf	IQ3_S	3.43GB
Llama-3.1-8B-Ultra-Instruct.Q3_K_S.gguf	Q3_K_S	3.41GB
Llama-3.1-8B-Ultra-Instruct.IQ3_M.gguf	IQ3_M	3.52GB
Llama-3.1-8B-Ultra-Instruct.Q3_K.gguf	Q3_K	3.74GB
Llama-3.1-8B-Ultra-Instruct.Q3_K_M.gguf	Q3_K_M	3.74GB
Llama-3.1-8B-Ultra-Instruct.Q3_K_L.gguf	Q3_K_L	4.03GB
Llama-3.1-8B-Ultra-Instruct.IQ4_XS.gguf	IQ4_XS	4.18GB
Llama-3.1-8B-Ultra-Instruct.Q4_0.gguf	Q4_0	4.34GB
Llama-3.1-8B-Ultra-Instruct.IQ4_NL.gguf	IQ4_NL	4.38GB
Llama-3.1-8B-Ultra-Instruct.Q4_K_S.gguf	Q4_K_S	4.37GB
Llama-3.1-8B-Ultra-Instruct.Q4_K.gguf	Q4_K	4.58GB
Llama-3.1-8B-Ultra-Instruct.Q4_K_M.gguf	Q4_K_M	4.58GB
Llama-3.1-8B-Ultra-Instruct.Q4_1.gguf	Q4_1	4.78GB
Llama-3.1-8B-Ultra-Instruct.Q5_0.gguf	Q5_0	5.21GB
Llama-3.1-8B-Ultra-Instruct.Q5_K_S.gguf	Q5_K_S	5.21GB
Llama-3.1-8B-Ultra-Instruct.Q5_K.gguf	Q5_K	5.34GB
Llama-3.1-8B-Ultra-Instruct.Q5_K_M.gguf	Q5_K_M	5.34GB
Llama-3.1-8B-Ultra-Instruct.Q5_1.gguf	Q5_1	5.65GB
Llama-3.1-8B-Ultra-Instruct.Q6_K.gguf	Q6_K	6.14GB
Llama-3.1-8B-Ultra-Instruct.Q8_0.gguf	Q8_0	7.95GB

Original model description:

license: llama3 library_name: transformers tags:

mergekit
merge base_model:
nbeerbower/llama3.1-gutenberg-8B
akjindal53244/Llama-3.1-Storm-8B
NousResearch/Meta-Llama-3.1-8B
nbeerbower/llama3.1-airoboros3.2-QDT-8B
Sao10K/Llama-3.1-8B-Stheno-v3.4 model-index:
name: Llama-3.1-8B-Ultra-Instruct 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: 80.81 name: strict accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Dampfinchen/Llama-3.1-8B-Ultra-Instruct 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: 32.49 name: normalized accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Dampfinchen/Llama-3.1-8B-Ultra-Instruct 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: 14.95 name: exact match source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Dampfinchen/Llama-3.1-8B-Ultra-Instruct 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: 5.59 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Dampfinchen/Llama-3.1-8B-Ultra-Instruct 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: 8.61 name: acc_norm source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Dampfinchen/Llama-3.1-8B-Ultra-Instruct 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: 31.4 name: accuracy source: url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Dampfinchen/Llama-3.1-8B-Ultra-Instruct name: Open LLM Leaderboard

merge

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 NousResearch/Meta-Llama-3.1-8B 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

models:
  - model: Sao10K/Llama-3.1-8B-Stheno-v3.4
    parameters:
      weight: 0.2
      density: 0.5
  - model: akjindal53244/Llama-3.1-Storm-8B
    parameters:
      weight: 0.5
      density: 0.5
  - model: nbeerbower/llama3.1-gutenberg-8B
    parameters:
      weight: 0.3
      density: 0.5
  - model: nbeerbower/llama3.1-airoboros3.2-QDT-8B
    parameters:
      weight: 0.2
      density: 0.5
merge_method: dare_ties
base_model: NousResearch/Meta-Llama-3.1-8B
dtype: bfloat16
name: Llama-3.1-8B-Ultra-Instruct

Use Llama 3 Instruct prompt template. Use with caution, I'm not responsible for what you do with it. All credits and thanks go to the creators of the fine tunes I've merged. In my own tests and on HF Eval it performs very well for a 8B model and I can recommend it. High quality quants by Bartowski: https://huggingface.co/bartowski/Llama-3.1-8B-Ultra-Instruct-GGUF

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	28.98
IFEval (0-Shot)	80.81
BBH (3-Shot)	32.49
MATH Lvl 5 (4-Shot)	14.95
GPQA (0-shot)	5.59
MuSR (0-shot)	8.61
MMLU-PRO (5-shot)	31.40

RichardErkhov/Dampfinchen_-_Llama-3.1-8B-Ultra-Instruct-gguf