README.md

---
license: apache-2.0
tags:
- moe
- merge
- mergekit
- lazymergekit
- MediaTek-Research/Breeze-7B-Instruct-v0.1
- augmxnt/shisa-7b-v1
- beomi/OPEN-SOLAR-KO-10.7B
language:
- zh
- ja
- ko
- tw
---

# EastAsia-4x7B-Moe-experiment

EastAsia-4x7B-Moe-experiment is a Mixure of Experts (MoE) made with the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [MediaTek-Research/Breeze-7B-Instruct-v0.1](https://huggingface.co/MediaTek-Research/Breeze-7B-Instruct-v0.1)
* [augmxnt/shisa-7b-v1](https://huggingface.co/augmxnt/shisa-7b-v1)
* [beomi/OPEN-SOLAR-KO-10.7B](https://huggingface.co/beomi/OPEN-SOLAR-KO-10.7B)

## 🧩 Configuration

```yaml
gate_mode: hidden
dtype: bfloat16
base_model: mlabonne/Marcoro14-7B-slerp
experts:
  - source_model: MediaTek-Research/Breeze-7B-Instruct-v0.1
    positive_prompts:
    - "翻譯"
  - source_model: augmxnt/shisa-7b-v1
    positive_prompts:
    - "翻訳"
  - source_model: beomi/OPEN-SOLAR-KO-10.7B
    positive_prompts:
    - "번역"
```

## 💻 Usage

```python
!pip install -qU transformers bitsandbytes accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "Heng666/EastAsia-4x7B-Moe-experiment"

tokenizer = AutoTokenizer.from_pretrained(model)
pipeline = transformers.pipeline(
    "text-generation",
    model=model,
    model_kwargs={"torch_dtype": torch.float16, "load_in_4bit": True},
)

messages = [{"role": "user", "content": "Explain what a Mixture of Experts is in less than 100 words."}]
prompt = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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"])
```