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---
language:
- ko

library_name: transformers
pipeline_tag: text-generation
license: cc-by-nc-4.0
---

# **Synatra-7B-v0.3-RP🐧**  
![Synatra-7B-v0.3-RP](./Synatra.png)

## Support Me
μ‹œλ‚˜νŠΈλΌλŠ” 개인 ν”„λ‘œμ νŠΈλ‘œ, 1인의 μžμ›μœΌλ‘œ 개발되고 μžˆμŠ΅λ‹ˆλ‹€. λͺ¨λΈμ΄ λ§ˆμŒμ— λ“œμ…¨λ‹€λ©΄ μ•½κ°„μ˜ 연ꡬ비 지원은 μ–΄λ–¨κΉŒμš”?
[<img src="https://cdn.buymeacoffee.com/buttons/default-orange.png" alt="Buy me a Coffee" width="217" height="50">](https://www.buymeacoffee.com/mwell)

Wanna be a sponser? Contact me on Telegram **AlzarTakkarsen**

# **License**

This model is strictly [*non-commercial*](https://creativecommons.org/licenses/by-nc/4.0/) (**cc-by-nc-4.0**) use only.
The "Model" is completely free (ie. base model, derivates, merges/mixes) to use for non-commercial purposes as long as the the included **cc-by-nc-4.0** license in any parent repository, and the non-commercial use statute remains, regardless of other models' licences. 
The licence can be changed after new model released. If you are to use this model for commercial purpose, Contact me.

# **Model Details**
**Base Model**  
[mistralai/Mistral-7B-Instruct-v0.1](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1)    

**Trained On**  
A6000 48GB * 8

**Instruction format**

It follows [ChatML](https://github.com/openai/openai-python/blob/main/chatml.md) format.

**TODO**

- ~~``RP 기반 νŠœλ‹ λͺ¨λΈ μ œμž‘``~~ βœ…
- ~~``데이터셋 μ •μ œ``~~ βœ…
- μ–Έμ–΄ 이해λŠ₯λ ₯ κ°œμ„ 
- ~~``상식 보완``~~ βœ…
- ν† ν¬λ‚˜μ΄μ € λ³€κ²½


# **Model Benchmark**

## Ko-LLM-Leaderboard

On Benchmarking...

# **Implementation Code**

Since, chat_template already contains insturction format above.
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("maywell/Synatra-7B-v0.3-RP")
tokenizer = AutoTokenizer.from_pretrained("maywell/Synatra-7B-v0.3-RP")

messages = [
    {"role": "user", "content": "λ°”λ‚˜λ‚˜λŠ” μ›λž˜ ν•˜μ–€μƒ‰μ΄μ•Ό?"},
]

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])
```

# Why It's benchmark score is lower than preview version?

**Apparently**, Preview model uses Alpaca Style prompt which has no pre-fix. But ChatML do.
# [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_maywell__Synatra-7B-v0.3-RP)

| Metric                | Value                     |
|-----------------------|---------------------------|
| Avg.                  | 57.38   |
| ARC (25-shot)         | 62.2          |
| HellaSwag (10-shot)   | 82.29    |
| MMLU (5-shot)         | 60.8         |
| TruthfulQA (0-shot)   | 52.64   |
| Winogrande (5-shot)   | 76.48   |
| GSM8K (5-shot)        | 21.15        |
| DROP (3-shot)         | 46.06         |