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Model: QuantFactory/llama-3.1-Asian-Bllossom-8B-Translator-GGUF Source: Original Platform
2026-04-10 11:19:02 +08:00
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+
+---
+
+library_name: transformers
+license: llama3.1
+language:
+- ko
+- vi
+- id
+- km
+- th
+metrics:
+- bleu
+- rouge
+base_model:
+- meta-llama/Llama-3.1-8B-Instruct
+
+---
+
+[![QuantFactory Banner](https://lh7-rt.googleusercontent.com/docsz/AD_4nXeiuCm7c8lEwEJuRey9kiVZsRn2W-b4pWlu3-X534V3YmVuVc2ZL-NXg2RkzSOOS2JXGHutDuyyNAUtdJI65jGTo8jT9Y99tMi4H4MqL44Uc5QKG77B0d6-JfIkZHFaUA71-RtjyYZWVIhqsNZcx8-OMaA?key=xt3VSDoCbmTY7o-cwwOFwQ)](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))
+```
+
+
+## Contributor
+- 원인호 (wih1226@seoultech.ac.kr)
+- 김민준 (mjkmain@seoultech.ac.kr)
+
+
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