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maywell
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Synatra-7B-v0.3-dpo

Text Generation
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PyTorch
mistral
conversational
text-generation-inference
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Synatra-7B-v0.3-dpo
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---
license: apache-2.0
---

# **Synatra-7B-v0.3-dpo🐧**  
![Synatra-7B-v0.3-dpo](./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? (Please) Contact me on Telegram **AlzarTakkarsen**

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

**Trained On**  
A100 80GB * 1

**Instruction format**

It follows [ChatML](https://github.com/openai/openai-python/blob/main/chatml.md) format and **Alpaca(No-Input)** format.

# **Model Benchmark**

## KOBEST_BOOLQ, SENTINEG, WIC - ZERO_SHOT
[EleutherAI/lm-evaluation-harness](https://github.com/EleutherAI/lm-evaluation-harness/tree/polyglot)λ₯Ό μ‚¬μš©ν•˜μ—¬ BoolQ, SentiNeg, Wic을 μΈ‘μ •ν–ˆμŠ΅λ‹ˆλ‹€.

| Model | COPA | HellaSwag | BoolQ | SentiNeg
| --- | --- | --- | --- | ---
| EleutherAI/polyglot-ko-12.8b | 0.7937 | 0.5954 | 0.4818 | 0.9117
| Synatra-7B-v0.3-base | 0.6344 | 0.5140 | 0.5226 | NaN
| **Synatra-7B-v0.3-dpo** | **0.6380** | **0.4780** | **0.8058** | **0.8942**

## 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-dpo")
tokenizer = AutoTokenizer.from_pretrained("maywell/Synatra-7B-v0.3-dpo")

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])
```
# [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-dpo)

| Metric                | Value                     |
|-----------------------|---------------------------|
| Avg.                  | 53.14   |
| ARC (25-shot)         | 62.8          |
| HellaSwag (10-shot)   | 82.58    |
| MMLU (5-shot)         | 61.46         |
| TruthfulQA (0-shot)   | 56.46   |
| Winogrande (5-shot)   | 76.24   |
| GSM8K (5-shot)        | 23.73        |
| DROP (3-shot)         | 8.68         |