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---
license: cc-by-nc-sa-4.0
datasets:
- squarelike/sharegpt_deepl_ko_translation
language:
- ko
pipeline_tag: translation
tags:
- translate
---
# **Seagull-13b-translation π**
![Seagull-typewriter](./Seagull-typewriter.png)
**Seagull-13b-translation** is yet another translator model, but carefully considered the following issues with existing translation models.
- `newline` or `space` not matching the original text
- Using translated dataset with first letter removed for training
- Codes
- Markdown format
- LaTeX format
- etc
μ΄λ° μ΄μλ€μ μΆ©λΆν 체ν¬νκ³ νμ΅μ μ§ννμμ§λ§, λͺ¨λΈμ μ¬μ©ν λλ μ΄λ° λΆλΆμ λν κ²°κ³Όλ₯Ό λ©΄λ°νκ² μ΄ν΄λ³΄λ κ²μ μΆμ²ν©λλ€(μ½λκ° ν¬ν¨λ ν
μ€νΈ λ±). λν κ°λ λ¬Έμ₯ λ°λ³΅ νμμ΄ μκΈΈ μ μμΌλ, νμ²λ¦¬ λ¨κ³μμ ν
μ€νΈνλ κ²μ μΆμ²ν©λλ€.
> If you're interested in building large-scale language models to solve a wide variety of problems in a wide variety of domains, you should consider joining [Allganize](https://allganize.career.greetinghr.com/o/65146).
For a coffee chat or if you have any questions, please do not hesitate to contact me as well! - kuotient.dev@gmail.com
This model was created as a personal experiment, unrelated to the organization I work for.
# **License**
## From original model author:
- Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International Public License, under LLAMA 2 COMMUNITY LICENSE AGREEMENT
- Full License available at: https://huggingface.co/beomi/llama-2-koen-13b/blob/main/LICENSE
# **Model Details**
#### **Developed by**
Jisoo Kim(kuotient)
#### **Base Model**
[beomi/llama-2-koen-13b](https://huggingface.co/beomi/llama-2-koen-13b)
#### **Datasets**
- [sharegpt_deepl_ko_translation](https://huggingface.co/datasets/squarelike/sharegpt_deepl_ko_translation)
- AIHUB
- κΈ°μ κ³Όν λΆμΌ ν-μ λ²μ λ³λ ¬ λ§λμΉ λ°μ΄ν°
- μΌμμν λ° κ΅¬μ΄μ²΄ ν-μ λ²μ λ³λ ¬ λ§λμΉ λ°μ΄ν°
## Usage
#### Format
It follows only **ChatML** format.
```python
<|im_start|>system
μ£Όμ΄μ§ λ¬Έμ₯μ νκ΅μ΄λ‘ λ²μνμΈμ.<|im_end|>
<|im_start|>user
{instruction}<|im_end|>
<|im_start|>assistant
```
```python
<|im_start|>system
μ£Όμ΄μ§ λ¬Έμ₯μ μμ΄λ‘ λ²μνμΈμ.<|im_end|>
<|im_start|>user
{instruction}<|im_end|>
<|im_start|>assistant
```
#### Example 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("kuotient/Seagull-13B-translation")
tokenizer = AutoTokenizer.from_pretrained("kuotient/Seagull-13B-translation")
messages = [
{"role": "user", "content": "λ°λλλ μλ νμμμ΄μΌ?"},
]
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])
``` |