File size: 5,268 Bytes
3356903 3eb93dd 3356903 3eb93dd 3356903 ddb5d59 3356903 028be72 3356903 028be72 3356903 9fd1bb6 3356903 028be72 3356903 f7034e4 3356903 f7034e4 3356903 3eb93dd |
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 |
---
license: other
library_name: transformers
tags:
- mergekit
- merge
- not-for-all-audiences
base_model:
- Nitral-AI/Infinitely-Laydiculous-7B
model-index:
- name: Infinite-Laymons-9B
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: 65.61
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ABX-AI/Infinite-Laymons-9B
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: 84.14
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ABX-AI/Infinite-Laymons-9B
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: 64.53
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ABX-AI/Infinite-Laymons-9B
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: 54.87
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ABX-AI/Infinite-Laymons-9B
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: 80.82
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ABX-AI/Infinite-Laymons-9B
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: 53.75
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=ABX-AI/Infinite-Laymons-9B
name: Open LLM Leaderboard
---
# GGUF / IQ / Imatrix for [Infinite-Laymons-9B](https://huggingface.co/ABX-AI/Infinite-Laymons-9B)
![image/png](https://cdn-uploads.huggingface.co/production/uploads/65d936ad52eca001fdcd3245/_Tgq278Uqjns2W0ug1kXE.png)
**Why Importance Matrix?**
**Importance Matrix**, at least based on my testing, has shown to improve the output and performance of "IQ"-type quantizations, where the compression becomes quite heavy.
The **Imatrix** performs a calibration, using a provided dataset. Testing has shown that semi-randomized data can help perserve more important segments as the compression is applied.
Related discussions in Github:
[[1]](https://github.com/ggerganov/llama.cpp/discussions/5006) [[2]](https://github.com/ggerganov/llama.cpp/discussions/5263#discussioncomment-8395384)
The imatrix.txt file that I used contains general, semi-random data, with some custom kink.
# Infinite-Laymons-9B
Infinite-Laymons-9B is intended for fictional role-play and storytelling.
The focus is on original responses and elimitation, or reduction of refusals.
## Merge Details
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
### Merge Method
This model was merged using the passthrough merge method.
### Models Merged
The following models were included in the merge:
* [Nitral-AI/Infinitely-Laydiculous-7B](https://huggingface.co/Nitral-AI/Infinitely-Laydiculous-7B)
* [ABX-AI/Infinite-Laymons-7B](https://huggingface.co/ABX-AI/Infinite-Laymons-7B)
### Configuration
The following YAML configuration was used to produce this model:
```yaml
slices:
- sources:
- model: Nitral-AI/Infinitely-Laydiculous-7B
layer_range: [0, 20]
- sources:
- model: ABX-AI/Infinite-Laymons-7B
layer_range: [12, 32]
merge_method: passthrough
dtype: float16
```
# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_ABX-AI__Infinite-Laymons-9B)
| Metric |Value|
|---------------------------------|----:|
|Avg. |67.29|
|AI2 Reasoning Challenge (25-Shot)|65.61|
|HellaSwag (10-Shot) |84.14|
|MMLU (5-Shot) |64.53|
|TruthfulQA (0-shot) |54.87|
|Winogrande (5-shot) |80.82|
|GSM8k (5-shot) |53.75| |