File size: 7,465 Bytes
06a0c26 7db9fb5 62b7ece 9f36e7e 67ffc69 8ea67d8 1fecf4d 8ea67d8 836db23 8ea67d8 06a0c26 62b7ece 70ae104 ca94405 090a4b9 fd534d8 090a4b9 58b4eaa fd534d8 ca94405 d521e6e b1d0633 d521e6e 62b7ece d787757 62b7ece 7db9fb5 5cdeebc 62b7ece 88958f0 62b7ece 67ffc69 62b7ece 67ffc69 62b7ece 67ffc69 62b7ece 4268c54 1fecf4d 4268c54 |
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 |
---
base_model:
- grimjim/kukulemon-7B
- Nitral-AI/Kunocchini-7b-128k-test
library_name: transformers
tags:
- mergekit
- merge
- alpaca
- mistral
license: cc-by-nc-4.0
model-index:
- name: Kunokukulemonchini-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: 66.72
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=icefog72/Kunokukulemonchini-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: 86.31
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=icefog72/Kunokukulemonchini-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: 65.31
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=icefog72/Kunokukulemonchini-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: 61.89
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=icefog72/Kunokukulemonchini-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: 78.45
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=icefog72/Kunokukulemonchini-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: 60.20
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=icefog72/Kunokukulemonchini-7b
name: Open LLM Leaderboard
---
# Kunokukulemonchini-7b
This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
Here is an 4.1bpw exl2 quant [Kunokukulemonchini-7b-4.1bpw-exl2](https://huggingface.co/icefog72/Kunokukulemonchini-7b-4.1bpw-exl2) for people like me with 6gb vram.
Thx to Natkituwu for
- 3.5bpw [Kunokukulemonchini-7b-3.5bpw-exl2](https://huggingface.co/Natkituwu/Kunokukulemonchini-7b-3.5bpw-exl2)
- 5.0bpw [Kunokukulemonchini-7b-5.0bpw-exl2](https://huggingface.co/Natkituwu/Kunokukulemonchini-7b-5.0bpw-exl2)
- 6.5bpw [Kunokukulemonchini-7b-6.5bpw-exl2](https://huggingface.co/Natkituwu/Kunokukulemonchini-7b-6.5bpw-exl2)
- 7.1bpw [Kunokukulemonchini-7b-7.1bpw-exl2](https://huggingface.co/Natkituwu/Kunokukulemonchini-7b-7.1bpw-exl2)
- 8.0bpw [Kunokukulemonchini-7b-8.0bpw-exl2](https://huggingface.co/Natkituwu/Kunokukulemonchini-7b-8.0bpw-exl2)
## Advertisement
- Check out new merge model [IceLemonTeaRP-32k-7b](https://huggingface.co/icefog72/IceLemonTeaRP-32k-7b)
## Merge Details
Slightly edited kukulemon-7B config.json before merge to get at least ~32k context window.
### Merge Method
This model was merged using the SLERP merge method.
### Models Merged
The following models were included in the merge:
* [grimjim/kukulemon-7B](https://huggingface.co/grimjim/kukulemon-7B)
* [Nitral-AI/Kunocchini-7b-128k-test](https://huggingface.co/Nitral-AI/Kunocchini-7b-128k-test)
## How to download, including from branches
### From the command line
I recommend using the `huggingface-hub` Python library:
```shell
pip3 install huggingface-hub
```
To download the `main` branch to a folder called `Kunokukulemonchini-7b`:
```shell
mkdir icefog72/Kunokukulemonchini-7b
huggingface-cli download icefog72/Kunokukulemonchini-7b --local-dir Kunokukulemonchini-7b --local-dir-use-symlinks False
```
<details>
<summary>More advanced huggingface-cli download usage</summary>
If you remove the `--local-dir-use-symlinks False` parameter, the files will instead be stored in the central Hugging Face cache directory (default location on Linux is: `~/.cache/huggingface`), and symlinks will be added to the specified `--local-dir`, pointing to their real location in the cache. This allows for interrupted downloads to be resumed, and allows you to quickly clone the repo to multiple places on disk without triggering a download again. The downside, and the reason why I don't list that as the default option, is that the files are then hidden away in a cache folder and it's harder to know where your disk space is being used, and to clear it up if/when you want to remove a download model.
The cache location can be changed with the `HF_HOME` environment variable, and/or the `--cache-dir` parameter to `huggingface-cli`.
For more documentation on downloading with `huggingface-cli`, please see: [HF -> Hub Python Library -> Download files -> Download from the CLI](https://huggingface.co/docs/huggingface_hub/guides/download#download-from-the-cli).
To accelerate downloads on fast connections (1Gbit/s or higher), install `hf_transfer`:
```shell
pip3 install hf_transfer
```
And set environment variable `HF_HUB_ENABLE_HF_TRANSFER` to `1`:
```shell
mkdir FOLDERNAME
HF_HUB_ENABLE_HF_TRANSFER=1 huggingface-cli download MODEL --local-dir FOLDERNAME --local-dir-use-symlinks False
```
Windows Command Line users: You can set the environment variable by running `set HF_HUB_ENABLE_HF_TRANSFER=1` before the download command.
</details>
### Configuration
The following YAML configuration was used to produce this model:
```yaml
slices:
- sources:
- model: grimjim/kukulemon-7B
layer_range: [0, 32]
- model: Nitral-AI/Kunocchini-7b-128k-test
layer_range: [0, 32]
merge_method: slerp
base_model: Nitral-AI/Kunocchini-7b-128k-test
parameters:
t:
- filter: self_attn
value: [0, 0.5, 0.3, 0.7, 1]
- filter: mlp
value: [1, 0.5, 0.7, 0.3, 0]
- value: 0.5
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_icefog72__Kunokukulemonchini-7b)
| Metric |Value|
|---------------------------------|----:|
|Avg. |69.61|
|AI2 Reasoning Challenge (25-Shot)|66.72|
|HellaSwag (10-Shot) |86.31|
|MMLU (5-Shot) |65.31|
|TruthfulQA (0-shot) |61.89|
|Winogrande (5-shot) |78.45|
|GSM8k (5-shot) |60.20|
|