File size: 5,955 Bytes
f63df2e 448f026 00ad073 f63df2e d475d88 f63df2e 47795b0 f91aaca 47795b0 e6ad0da 47795b0 f63df2e e467c44 2fd1f62 f63df2e bea3651 f63df2e 2fd1f62 f63df2e 00ad073 |
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 |
---
language:
- id
- en
license: cc-by-nc-4.0
tags:
- merge
- mergekit
model-index:
- name: MiaLatte-Indo-Mistral-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: 66.55
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=indischepartij/MiaLatte-Indo-Mistral-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: 85.23
name: normalized accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=indischepartij/MiaLatte-Indo-Mistral-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: 63.93
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=indischepartij/MiaLatte-Indo-Mistral-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: 56.04
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=indischepartij/MiaLatte-Indo-Mistral-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: 80.35
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=indischepartij/MiaLatte-Indo-Mistral-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: 55.04
name: accuracy
source:
url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=indischepartij/MiaLatte-Indo-Mistral-7b
name: Open LLM Leaderboard
---
# MiaLatte-Indo-Mistral-7b
MiaLatte is a derivative model of [OpenMia](https://huggingface.co/indischepartij/OpenMia-Indo-Mistral-7b-v2), which is able to answer everyday questions specifically in Bahasa Indonesia (Indonesia Language).
some of GGUF: https://huggingface.co/indischepartij/MiaLatte-Indo-Mistral-7b-GGUF
# Examples
MiaLatte-Indo-Mistral-7b is a merge of the following models using MergeKit:
* [indischepartij/OpenMia-Indo-Mistral-7b-v2](https://huggingface.co/indischepartij/OpenMia-Indo-Mistral-7b-v2)
* [Obrolin/Kesehatan-7B-v0.1](https://huggingface.co/Obrolin/Kesehatan-7B-v0.1)
* [FelixChao/WestSeverus-7B-DPO-v2](https://huggingface.co/FelixChao/WestSeverus-7B-DPO-v2)
## 🪄 Open LLM Benchmark
## 🧩 Configuration
```yaml
slices:
models:
- model: indischepartij/OpenMia-Indo-Mistral-7b-v2
parameters:
density: 0.50
weight: 0.35
- model: Obrolin/Kesehatan-7B-v0.1
parameters:
density: 0.50
weight: 0.35
- model: FelixChao/WestSeverus-7B-DPO-v2
parameters:
density: 0.50
weight: 0.30
merge_method: dare_ties
base_model: indischepartij/OpenMia-Indo-Mistral-7b-v2
parameters:
int8_mask: true
dtype: float16
```
## 💻 Usage
```python
!pip install -qU transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "indischepartij/MiaLatte-Indo-Mistral-7b"
messages = [{"role": "user", "content": "Apa jenis skincare yang cocok untuk kulit berjerawat??"}]
tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
"text-generation",
model=model,
torch_dtype=torch.float16,
device_map="auto",
)
outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
```
# [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_indischepartij__MiaLatte-Indo-Mistral-7b)
| Metric |Value|
|---------------------------------|----:|
|Avg. |67.86|
|AI2 Reasoning Challenge (25-Shot)|66.55|
|HellaSwag (10-Shot) |85.23|
|MMLU (5-Shot) |63.93|
|TruthfulQA (0-shot) |56.04|
|Winogrande (5-shot) |80.35|
|GSM8k (5-shot) |55.04|
|