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---
language:
- en
license: cc-by-nc-sa-4.0
library_name: transformers
tags:
- moe
- merge
- MoE
pipeline_tag: text-generation
model-index:
- name: SOLARC-MOE-10.7Bx6
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: 70.9
name: normalized accuracy
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=DopeorNope/SOLARC-MOE-10.7Bx6
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: 88.4
name: normalized accuracy
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=DopeorNope/SOLARC-MOE-10.7Bx6
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: 66.36
name: accuracy
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=DopeorNope/SOLARC-MOE-10.7Bx6
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: 71.85
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=DopeorNope/SOLARC-MOE-10.7Bx6
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: 83.66
name: accuracy
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=DopeorNope/SOLARC-MOE-10.7Bx6
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: 64.9
name: accuracy
source:
url: https://huggingface.co./spaces/HuggingFaceH4/open_llm_leaderboard?query=DopeorNope/SOLARC-MOE-10.7Bx6
name: Open LLM Leaderboard
---
**The license is `cc-by-nc-sa-4.0`.**
# **🐻❄️SOLARC-MOE-10.7Bx6🐻❄️**
## Model Details
**Model Developers** Seungyoo Lee(DopeorNope)
I am in charge of Large Language Models (LLMs) at Markr AI team in South Korea.
**Input** Models input text only.
**Output** Models generate text only.
**Model Architecture**
SOLARC-MOE-10.7Bx6 is an auto-regressive language model based on the SOLAR architecture.
---
## **Base Model**
[kyujinpy/Sakura-SOLAR-Instruct](https://huggingface.co./kyujinpy/Sakura-SOLAR-Instruct)
[Weyaxi/SauerkrautLM-UNA-SOLAR-Instruct](https://huggingface.co./Weyaxi/SauerkrautLM-UNA-SOLAR-Instruct)
[VAGOsolutions/SauerkrautLM-SOLAR-Instruct](https://huggingface.co./VAGOsolutions/SauerkrautLM-SOLAR-Instruct)
[fblgit/UNA-SOLAR-10.7B-Instruct-v1.0](https://huggingface.co./fblgit/UNA-SOLAR-10.7B-Instruct-v1.0)
[jeonsworld/CarbonVillain-en-10.7B-v1](https://huggingface.co./jeonsworld/CarbonVillain-en-10.7B-v1)
## **Implemented Method**
I have built a model using the Mixture of Experts (MOE) approach, utilizing each of these models as the base.
I wanted to test if it was possible to compile with a non-power of 2, like with 6
---
# Implementation Code
## Load model
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
repo = "DopeorNope/SOLARC-MOE-10.7Bx6"
OpenOrca = AutoModelForCausalLM.from_pretrained(
repo,
return_dict=True,
torch_dtype=torch.float32,
device_map='auto'
)
OpenOrca_tokenizer = AutoTokenizer.from_pretrained(repo)
```
---
# [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_DopeorNope__SOLARC-MOE-10.7Bx6)
| Metric |Value|
|---------------------------------|----:|
|Avg. |74.35|
|AI2 Reasoning Challenge (25-Shot)|70.90|
|HellaSwag (10-Shot) |88.40|
|MMLU (5-Shot) |66.36|
|TruthfulQA (0-shot) |71.85|
|Winogrande (5-shot) |83.66|
|GSM8k (5-shot) |64.90|
|