File size: 5,748 Bytes
ed9e214 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 |
---
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
---
# QuantFactory/Llama-3.1-8B-Ultra-Instruct-GGUF
This is quantized version of [Dampfinchen/Llama-3.1-8B-Ultra-Instruct](https://huggingface.co/Dampfinchen/Llama-3.1-8B-Ultra-Instruct) created using llama.cpp
# Original Model Card
# merge
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
## Merge Details
### Merge Method
This model was merged using the [DARE](https://arxiv.org/abs/2311.03099) [TIES](https://arxiv.org/abs/2306.01708) merge method using [NousResearch/Meta-Llama-3.1-8B](https://huggingface.co/NousResearch/Meta-Llama-3.1-8B) as a base.
### Models Merged
The following models were included in the merge:
* [nbeerbower/llama3.1-gutenberg-8B](https://huggingface.co/nbeerbower/llama3.1-gutenberg-8B)
* [akjindal53244/Llama-3.1-Storm-8B](https://huggingface.co/akjindal53244/Llama-3.1-Storm-8B)
* [nbeerbower/llama3.1-airoboros3.2-QDT-8B](https://huggingface.co/nbeerbower/llama3.1-airoboros3.2-QDT-8B)
* [Sao10K/Llama-3.1-8B-Stheno-v3.4](https://huggingface.co/Sao10K/Llama-3.1-8B-Stheno-v3.4)
### 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](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_Dampfinchen__Llama-3.1-8B-Ultra-Instruct)
| 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|
|