Upload llama-3.1-Asian-Bllossom-8B-Translator.Q4_0_8_8.gguf with huggingface_hub
This commit is contained in:
ai-modelscope
184
README.md
184
README.md
@@ -1,47 +1,151 @@
|
||||
|
||||
---
|
||||
license: Apache License 2.0
|
||||
|
||||
#model-type:
|
||||
##如 gpt、phi、llama、chatglm、baichuan 等
|
||||
#- gpt
|
||||
library_name: transformers
|
||||
license: llama3.1
|
||||
language:
|
||||
- ko
|
||||
- vi
|
||||
- id
|
||||
- km
|
||||
- th
|
||||
metrics:
|
||||
- bleu
|
||||
- rouge
|
||||
base_model:
|
||||
- meta-llama/Llama-3.1-8B-Instruct
|
||||
|
||||
#domain:
|
||||
##如 nlp、cv、audio、multi-modal
|
||||
#- nlp
|
||||
|
||||
#language:
|
||||
##语言代码列表 https://help.aliyun.com/document_detail/215387.html?spm=a2c4g.11186623.0.0.9f8d7467kni6Aa
|
||||
#- cn
|
||||
|
||||
#metrics:
|
||||
##如 CIDEr、Blue、ROUGE 等
|
||||
#- CIDEr
|
||||
|
||||
#tags:
|
||||
##各种自定义，包括 pretrained、fine-tuned、instruction-tuned、RL-tuned 等训练方法和其他
|
||||
#- pretrained
|
||||
|
||||
#tools:
|
||||
##如 vllm、fastchat、llamacpp、AdaSeq 等
|
||||
#- vllm
|
||||
---
|
||||
### 当前模型的贡献者未提供更加详细的模型介绍。模型文件和权重，可浏览“模型文件”页面获取。
|
||||
#### 您可以通过如下git clone命令，或者ModelScope SDK来下载模型
|
||||
|
||||
SDK下载
|
||||
```bash
|
||||
#安装ModelScope
|
||||
pip install modelscope
|
||||
```
|
||||
```python
|
||||
#SDK模型下载
|
||||
from modelscope import snapshot_download
|
||||
model_dir = snapshot_download('QuantFactory/llama-3.1-Asian-Bllossom-8B-Translator-GGUF')
|
||||
```
|
||||
Git下载
|
||||
```
|
||||
#Git模型下载
|
||||
git clone https://www.modelscope.cn/QuantFactory/llama-3.1-Asian-Bllossom-8B-Translator-GGUF.git
|
||||
[](https://hf.co/QuantFactory)
|
||||
|
||||
|
||||
# QuantFactory/llama-3.1-Asian-Bllossom-8B-Translator-GGUF
|
||||
This is quantized version of [MLP-KTLim/llama-3.1-Asian-Bllossom-8B-Translator](https://huggingface.co/MLP-KTLim/llama-3.1-Asian-Bllossom-8B-Translator) created using llama.cpp
|
||||
|
||||
# Original Model Card
|
||||
|
||||
|
||||
# Model Card for Model ID
|
||||
|
||||
This model is a multilingual translation model fine-tuned on LLaMA 3.1 Instruct base model. It enables mutual translation between the following Southeast Asian languages:
|
||||
|
||||
- Korean
|
||||
- Vietnamese
|
||||
- Indonesian
|
||||
- Cambodian (Khmer)
|
||||
- Thai
|
||||
|
||||
## Acknowledgements
|
||||
AICA <img src="https://aica-gj.kr/images/logo.png" width="20%" height="20%">
|
||||
|
||||
## Model Details
|
||||
The model is designed for translating short text segments between any pair of the supported languages.
|
||||
|
||||
Supported language pairs:
|
||||
|
||||
- Korean ↔ Vietnamese
|
||||
- Korean ↔ Indonesian
|
||||
- Korean ↔ Cambodian
|
||||
- Korean ↔ Thai
|
||||
- Vietnamese ↔ Indonesian
|
||||
- Vietnamese ↔ Cambodian
|
||||
- Vietnamese ↔ Thai
|
||||
- Indonesian ↔ Cambodian
|
||||
- Indonesian ↔ Thai
|
||||
- Cambodian ↔ Thai
|
||||
|
||||
### Model Description
|
||||
|
||||
This model is specifically optimized for Southeast Asian language translation needs, focusing on enabling communication between these specific language communities.
|
||||
|
||||
The extensive training data of 20M examples (1M for each translation direction) provides a robust foundation for handling common expressions and basic conversations across these languages.
|
||||
|
||||
### Model Architecture
|
||||
|
||||
Base Model: meta-llama/Llama-3.1-8B-Instruct
|
||||
|
||||
|
||||
## Bias, Risks, and Limitations
|
||||
|
||||
- Performance is limited to short sentences and phrases
|
||||
- May not handle complex or lengthy text effectively
|
||||
- Translation quality may vary depending on language pair and content complexity
|
||||
|
||||
## Evaluation results
|
||||
|
||||
| Source Language | Target Language | BLEU Score | ROUGE-1 | ROUGE-L |
|
||||
|----------------|-----------------|------------|---------|---------|
|
||||
| Korean | Vietnamese | 56.70 | 81.64 | 76.66 |
|
||||
| Korean | Cambodian | 71.69 | 89.26 | 88.20 |
|
||||
| Korean | Indonesian | 58.32 | 80.39 | 76.63 |
|
||||
| Korean | Thai | 63.26 | 78.88 | 72.29 |
|
||||
| Vietnamese | Korean | 49.01 | 75.57 | 72.74 |
|
||||
| Vietnamese | Cambodian | 78.26 | 90.74 | 90.32 |
|
||||
| Vietnamese | Indonesian | 65.96 | 83.08 | 81.46 |
|
||||
| Vietnamese | Thai | 65.93 | 81.09 | 76.57 |
|
||||
| Cambodian | Korean | 49.10 | 72.67 | 69.75 |
|
||||
| Cambodian | Vietnamese | 63.42 | 81.56 | 79.09 |
|
||||
| Cambodian | Indonesian | 61.41 | 79.67 | 77.75 |
|
||||
| Cambodian | Thai | 70.91 | 81.85 | 77.66 |
|
||||
| Indonesian | Korean | 53.61 | 77.14 | 74.29 |
|
||||
| Indonesian | Vietnamese | 68.21 | 85.41 | 83.10 |
|
||||
| Indonesian | Cambodian | 78.84 | 90.81 | 90.35 |
|
||||
| Indonesian | Thai | 67.12 | 81.54 | 77.19 |
|
||||
| Thai | Korean | 45.59 | 72.48 | 69.46 |
|
||||
| Thai | Vietnamese | 61.55 | 81.01 | 78.24 |
|
||||
| Thai | Cambodian | 78.52 | 91.47 | 91.16 |
|
||||
| Thai | Indonesian | 58.99 | 78.56 | 76.40 |
|
||||
|
||||
## Example
|
||||
|
||||
```py
|
||||
from transformers import AutoModelForCausalLM, AutoTokenizer
|
||||
|
||||
model = AutoModelForCausalLM.from_pretrained(
|
||||
"MLP-KTLim/llama-3.1-Asian-Bllossom-8B-Translator",
|
||||
torch_dtype="auto",
|
||||
device_map="auto",
|
||||
)
|
||||
|
||||
tokenizer = AutoTokenizer.from_pretrained(
|
||||
"MLP-KTLim/llama-3.1-Asian-Bllossom-8B-Translator",
|
||||
)
|
||||
|
||||
input_text = "안녕하세요? 아시아 언어 번역 모델 입니다."
|
||||
|
||||
def get_input_ids(source_lang, target_lang, message):
|
||||
assert source_lang in ["Korean", "Vietnamese", "Indonesian", "Thai", "Cambodian"]
|
||||
assert target_lang in ["Korean", "Vietnamese", "Indonesian", "Thai", "Cambodian"]
|
||||
|
||||
input_ids = tokenizer.apply_chat_template(
|
||||
conversation=[
|
||||
{"role": "system", "content": f"You are a useful translation AI. Please translate the sentence given in {source_lang} into {target_lang}."},
|
||||
{"role": "user", "content": message},
|
||||
],
|
||||
tokenize=True,
|
||||
return_tensors="pt",
|
||||
add_generation_prompt=True,
|
||||
)
|
||||
return input_ids
|
||||
|
||||
input_ids = get_input_ids(
|
||||
source_lang="Korean",
|
||||
target_lang="Vietnamese",
|
||||
message=input_text,
|
||||
)
|
||||
|
||||
output = model.generate(
|
||||
input_ids.to(model.device),
|
||||
max_new_tokens=128,
|
||||
)
|
||||
|
||||
print(tokenizer.decode(output[0][len(input_ids[0]):], skip_special_tokens=True))
|
||||
```
|
||||
|
||||
<p style="color: lightgrey;">如果您是本模型的贡献者，我们邀请您根据<a href="https://modelscope.cn/docs/ModelScope%E6%A8%A1%E5%9E%8B%E6%8E%A5%E5%85%A5%E6%B5%81%E7%A8%8B%E6%A6%82%E8%A7%88" style="color: lightgrey; text-decoration: underline;">模型贡献文档</a>，及时完善模型卡片内容。</p>
|
||||
|
||||
## Contributor
|
||||
- 원인호 (wih1226@seoultech.ac.kr)
|
||||
- 김민준 (mjkmain@seoultech.ac.kr)
|
||||
|
||||
|
||||
|
||||
Reference in New Issue
Block a user