Update README.md

README.md

@@ -1,199 +1,77 @@
 ---
+language:
+- en
+- ko
+license: llama3
 library_name: transformers
-tags: []
+tags:
+- translation
+- enko
+- ko
+base_model:
+- meta-llama/Meta-Llama-3-8B-Instruct
+datasets:
+- nayohan/aihub-en-ko-translation-1.2m
+pipeline_tag: text-generation
 ---
 
-# Model Card for Model ID
-
-<!-- Provide a quick summary of what the model is/does. -->
-
-
-
-## Model Details
-
-### Model Description
-
-<!-- Provide a longer summary of what this model is. -->
-
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
-
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
-
-### Model Sources [optional]
-
-<!-- Provide the basic links for the model. -->
-
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
-
-## Uses
-
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-
-### Direct Use
-
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
-
-[More Information Needed]
-
-### Downstream Use [optional]
-
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
-
-[More Information Needed]
-
-### Out-of-Scope Use
-
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-
-[More Information Needed]
-
-## Bias, Risks, and Limitations
-
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-
-[More Information Needed]
-
-### Recommendations
-
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
-
-## How to Get Started with the Model
-
-Use the code below to get started with the model.
-
-[More Information Needed]
-
-## Training Details
-
-### Training Data
-
-<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
-
-[More Information Needed]
-
-### Training Procedure
-
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
-
-#### Preprocessing [optional]
-
-[More Information Needed]
-
-
-#### Training Hyperparameters
-
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
-
-#### Speeds, Sizes, Times [optional]
-
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
-
-[More Information Needed]
-
-## Evaluation
-
-<!-- This section describes the evaluation protocols and provides the results. -->
-
-### Testing Data, Factors & Metrics
-
-#### Testing Data
-
-<!-- This should link to a Dataset Card if possible. -->
-
-[More Information Needed]
-
-#### Factors
-
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
-
-[More Information Needed]
-
-#### Metrics
-
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
-
-[More Information Needed]
-
-### Results
-
-[More Information Needed]
-
-#### Summary
-
-
-
-## Model Examination [optional]
-
-<!-- Relevant interpretability work for the model goes here -->
-
-[More Information Needed]
-
-## Environmental Impact
-
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-
-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
-
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
-
-## Technical Specifications [optional]
-
-### Model Architecture and Objective
-
-[More Information Needed]
-
-### Compute Infrastructure
-
-[More Information Needed]
-
-#### Hardware
-
-[More Information Needed]
-
-#### Software
-
-[More Information Needed]
-
-## Citation [optional]
-
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
-
-**BibTeX:**
-
-[More Information Needed]
-
-**APA:**
-
-[More Information Needed]
-
-## Glossary [optional]
-
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
-
-[More Information Needed]
-
-## More Information [optional]
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-[More Information Needed]
-
-## Model Card Authors [optional]
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-[More Information Needed]
-
-## Model Card Contact
-
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+# **Introduction**
+This model was trained to translate a sentence from English to Korean using the 486k dataset from [squarelike/sharegpt_deepl_ko_translation](https://huggingface.co/datasets/nayohan/aihub-en-ko-translation-1.2m).
+
+### **Loading the Model**
+
+Use the following Python code to load the model:
+
+```python
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model_name = "nayohan/llama3-8b-it-translation-sharegpt-en-ko"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(
+  model_name,
+  device_map="auto",
+  torch_dtype=torch.bfloat16
+)
+```
+
+### **Generating Text**
+This model supports translation from English to Korean. To generate text, use the following Python code: 
+```python
+system_prompt="당신은 번역기 입니다. 영어를 한국어로 번역하세요."
+sentence = "The aerospace industry is a flower in the field of technology and science."
+conversation = [{'role': 'system', 'content': system_prompt},
+                {'role': 'user', 'content': sentence}]
+
+inputs = tokenizer.apply_chat_template(
+  conversation,
+  tokenize=True,
+  add_generation_prompt=True,
+  return_tensors='pt'
+).to("cuda")
+
+outputs = model.generate(inputs, 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  colloquial 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: 항공우주 산업은 기술과 과학 분야의 꽃입니다.<|eot_id|>
+
+# INPUT:
+<|begin_of_text|><|start_header_id|>system<|end_header_id|>\n\n당신은 번역기 입니다. 영어를 한국어로 번역하세요.<|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: 기술 및 기초 과학은 연구 측면에서 매우 중요합니다. 이는 한 국가의 산업 발전에 큰 영향을 미칩니다. 정부 정책은 연구 예산을 통제합니다.<|eot_id|>
+
+```
+
+### **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]