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---
license: apache-2.0
tags:
- moe
- frankenmoe
- merge
- mergekit
- lazymergekit
- yanolja/KoSOLAR-10.7B-v0.2
- yanolja/Bookworm-10.7B-v0.4-DPO
base_model:
- yanolja/KoSOLAR-10.7B-v0.2
- yanolja/Bookworm-10.7B-v0.4-DPO
---

# solar_merge_test_1

## ๐Ÿงฉ Configuration

```yaml
base_model: yanolja/KoSOLAR-10.7B-v0.2
dtype: float16
experts:
  - source_model: yanolja/KoSOLAR-10.7B-v0.2
    positive_prompts: ["๋‹น์‹ ์€ ์‚ฌ๋žŒ๋“ค์—๊ฒŒ ๋„์›€์„ ์ฃผ๋Š” ์–ด์‹œ์Šคํ„ดํŠธ์ด๋‹ค."]
  - source_model: yanolja/Bookworm-10.7B-v0.4-DPO
    positive_prompts: ["๋‹น์‹ ์€ ๋‹ค๋ฐฉ๋ฉด์œผ๋กœ ๋‹ต๋ณ€์„ ์ž˜ํ•˜๋Š” ์–ด์‹œ์Šคํ„ดํŠธ์ด๋‹ค."]
gate_mode: cheap_embed
tokenizer_source: base
```

## ๐Ÿ’ป Usage

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

from transformers import AutoTokenizer
import transformers
import torch

model = "jieunhan/solar_merge_test_3"

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"])
```