nayohan
/

llama3-8b-it-translation-tech-en-ko-1sent

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 ---
 library_name: transformers
-tags: []
 ---
-# Model Card for Model ID
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 ---
+language:
+- en
+- ko
+license: llama2
 library_name: transformers
+tags:
+- tech
+- translation
+- enko
+- ko
+base_model:
+- meta-llama/Meta-Llama-3-8B-Instruct
+datasets:
+- nayohan/026_tech_translation
+pipeline_tag: text-generation
 ---
+# **Introduction**
+This model is trained to translate single sentences from English to Korean in a domain related to technology science.
+### **Loading the Model**
+Use the following Python code to load the model:
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+model_name = "nayohan/llama3-8b-translation-en-ko-1sent"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name,device_map="auto",torch_dtype=torch.float16)
+```
+### **Generating Text**
+To generate text, use the following Python code: No support for other languages or reverse direction and styles at this time.
+```python
+source="en"
+target="ko"
+style="written"
+SYSTEM_PROMPT=f"Acts as a translator. Translate {source} sentences into {target} sentences in {style} style."
+s = "The aerospace industry is a flower in the field of technology and science."
+conversation = [{'role': 'system', 'content': SYSTEM_PROMPT},
+                {'role': 'user', 'content': s}]
+inputs = tokenizer.apply_chat_template(conversation,tokenize=True,add_generation_prompt=True,return_tensors='pt').to("cuda")
+outputs = model.generate(inputs, early_stopping=True, max_new_tokens=256)
+print(tokenizer.decode(outputs[0][len(inputs[0]):]))
+```
+```
+# Result
+# INPUT: <|begin_of_text|><|start_header_id|>system<|end_header_id|>\n\nActs as a translator. Translate en sentences into ko sentences in written style.<|eot_id|><|start_header_id|>user<|end_header_id|>\n\nThe aerospace industry is a flower in the field of technology and science.<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n
+# OUTPUT: 항공 우주 산업은 기술과 과학 분야의 꽃이라고 할 수 있다.
+## [Warning!] In multiple sentences, there is a tendency to output in a single sentence.
+# INPUT: <|begin_of_text|><|start_header_id|>system<|end_header_id|>\n\nActs as a translator. Translate ko sentences into en sentences in written style.<|eot_id|><|start_header_id|>user<|end_header_id|>\n\n
+Technical and basic sciences are very important in terms of research. It has a significant impact on the industrial development of a country. Government policies control the research budget.<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n
+# OUTPUT: 연구 측면에서 기술 및 기초 과학은 국가의 산업 발전에 큰 영향을 미치며 정부 정책은 연구 예산을 통제한다.
+```
+### **Citation**
+```bibtex
+@article{llama3modelcard,
+        title={Llama 3 Model Card},
+        author={AI@Meta},
+        year={2024},
+        url={https://github.com/meta-llama/llama3/blob/main/MODEL_CARD.md}
+}
+```
+Our trainig code can be found here: [TBD]