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---
tags:
- text-generation
license: cc-by-nc-4.0
language:
- ko
base_model: yanolja/Bookworm-10.7B-v0.4-DPO
pipeline_tag: text-generation
---
# **DataVortexS-10.7B-dpo-v1.4**
<img src="./DataVortex.png" alt="DataVortex" style="height: 8em;">
## **Model Details**
### **Base Model**
[yanolja/Bookworm-10.7B-v0.4-DPO](https://huggingface.co/yanolja/Bookworm-10.7B-v0.4-DPO)
### **Trained On**
- **OS**: Ubuntu 22.04
- **GPU**: H100 80GB 4ea
- **transformers**: v4.36.2
### **Instruction format**
It follows **ChatML** format.
E.g.
```python
text = """\
<|im_start|>system
당신은 μ‚¬λžŒλ“€μ΄ 정보λ₯Ό 찾을 수 μžˆλ„λ‘ λ„μ™€μ£ΌλŠ” 인곡지λŠ₯ λΉ„μ„œμž…λ‹ˆλ‹€.<|im_end|>
<|im_start|>user
λŒ€ν•œλ―Όκ΅­μ˜ μˆ˜λ„λŠ” μ–΄λ””μ•Ό?<|im_end|>
<|im_start|>assistant
λŒ€ν•œλ―Όκ΅­μ˜ μˆ˜λ„λŠ” μ„œμšΈμž…λ‹ˆλ‹€.<|im_end|>
<|im_start|>user
μ„œμšΈ μΈκ΅¬λŠ” 총 λͺ‡ λͺ…이야?<|im_end|>
<|im_start|>assistant
"""
```
## **Model Benchmark**
### **[Ko LM Eval Harness](https://github.com/Beomi/ko-lm-evaluation-harness)**
| Task | 0-shot | 5-shot | 10-shot | 50-shot |
| :--------------- | -----------: | -----------: | -----------: | -----------: |
| kobest_boolq | 0.757911 | 0.907177 | 0.924496 | 0.605075 |
| kobest_copa | 0.740605 | 0.801886 | 0.831886 | 0.849978 |
| kobest_hellaswag | 0.445176 | 0.454788 | 0.468654 | 0.45218 |
| kobest_sentineg | 0.415445 | 0.95214 | 0.962217 | 0.967254 |
| **Average** | **0.589784** | **0.778998** | **0.796813** | **0.718622** |
### **[Ko-LLM-Leaderboard](https://huggingface.co/spaces/upstage/open-ko-llm-leaderboard)**
| Average | Ko-ARC | Ko-HellaSwag | Ko-MMLU | Ko-TruthfulQA | Ko-CommonGen V2 |
| ------: | -----: | -----------: | ------: | ------------: | --------------: |
| 53.81 | 52.05 | 62.93 | 53.59 | 50.42 | 50.06 |
## **Implementation Code**
This model contains the chat_template instruction format.
You can use the code below.
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
device = "cuda" # the device to load the model onto
model = AutoModelForCausalLM.from_pretrained("Edentns/DataVortexS-10.7B-dpo-v1.4")
tokenizer = AutoTokenizer.from_pretrained("Edentns/DataVortexS-10.7B-dpo-v1.4")
messages = [
{"role": "system", "content": "당신은 μ‚¬λžŒλ“€μ΄ 정보λ₯Ό 찾을 수 μžˆλ„λ‘ λ„μ™€μ£ΌλŠ” 인곡지λŠ₯ λΉ„μ„œμž…λ‹ˆλ‹€."},
{"role": "user", "content": "λŒ€ν•œλ―Όκ΅­μ˜ μˆ˜λ„λŠ” μ–΄λ””μ•Ό?"},
{"role": "assistant", "content": "λŒ€ν•œλ―Όκ΅­μ˜ μˆ˜λ„λŠ” μ„œμšΈμž…λ‹ˆλ‹€."},
{"role": "user", "content": "μ„œμšΈ μΈκ΅¬λŠ” 총 λͺ‡ λͺ…이야?"}
]
encodeds = tokenizer.apply_chat_template(messages, return_tensors="pt")
model_inputs = encodeds.to(device)
model.to(device)
generated_ids = model.generate(model_inputs, max_new_tokens=1000, do_sample=True)
decoded = tokenizer.batch_decode(generated_ids)
print(decoded[0])
```
## **License**
This model is licensed under the [cc-by-nc-4.0](https://creativecommons.org/licenses/by-nc/4.0/). which allows others to share and adapt the model for non-commercial purposes.
<div align="center">
<a href="https://edentns.com/">
<img src="./Logo.png" alt="Logo" style="height: 3em;">
</a>
</div>