Sold by: LG CNSÂ
Deployed on AWS
The first open model in the family of Large Language Models (LLMs) developed by LG AI Research.
Overview
EXAONE stands for EXpert AI for EveryONE, a vision that LG is committed to realizing in order to democratize access to expert-level artificial intelligence capabilities. What makes the EXAONE 3.0 truly revolutionary is its integration of advanced deep learning algorithms that enable dynamic adaptation to evolving data sets. This flexibility ensures ongoing improvements in the system's predictive analytics and decision-making abilities, establishing a new standard for AI models. LG AI Research plans to continue enriching the EXAONE’s capabilities by incorporating data from over 100 million sources across disciplines like law, biology, medicine, and education. With diverse model scales tailored to different applications, EXAONE promises to revolutionize the AI landscape and drive innovation across industries.
Highlights
- **Excellent Performance in Korean ** EXAONE 3.0 has a competitive overall performance in English against the comparison models, smaller than 20B while it shows an excellent performance in Korean. The EXAONE language model is a bilingual model trained mainly on English and Korean. As trace amounts of other languages are also included in the training data, output content can be generated in other languages, but the performance is very limited.**
- **Rigorous Data Compliance** LG AI Research conducts AI Compliance reviews throughout the entire process of data collection, AI model training, and information provision. Each training dataset is subjected to a licensing review process. After this review, the AI model is trained using the approved data. Subsequently, a data risk assessment is conducted to establish the criteria for the AI model’s distribution. The language model, developed pursuant to this robust compliance system, distinctly omits legally precarious data such as news articles and books.
- **Trustworthy AI through Responsible Practices** We have strived to develop and deploy EXAONE models responsibly in accordance with the LG AI Ethics Principles. Throughout the entire model development process, we performed an AI ethics impact assessment to mitigate potential risks and create a reliable model. We have followed the LG AI Ethics Principles to ensure the responsible development and deployment of the EXAONE 3.0 7.8B instruction-tuned model. We focused on improving the model’s safety and maintaining high ethical standards throughout the development process.
Details
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Delivery method
Latest version
Deployed on AWS
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Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/host/hour |
|---|---|---|
ml.g5.2xlarge Inference (Batch) Recommended | Model inference on the ml.g5.2xlarge instance type, batch mode | $3.197 |
ml.g5.4xlarge Inference (Real-Time) Recommended | Model inference on the ml.g5.4xlarge instance type, real-time mode | $4.283 |
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Delivery details
Amazon SageMaker model
An Amazon SageMaker model package is a pre-trained machine learning model ready to use without additional training. Use the model package to create a model on Amazon SageMaker for real-time inference or batch processing. Amazon SageMaker is a fully managed platform for building, training, and deploying machine learning models at scale.
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Version release notes
EXAONE v3.0.0 demonstrates highly competitive real-world performance with instruction-following capability against other state-of-the-art open models of similar size. Our comparative analysis shows that EXAONE v3.0.0 excels particularly in Korean, while achieving compelling performance across general tasks and complex reasoning.
Additional details
Inputs
- Summary
The model accepts JSON requests with parameters that can be used to control the generated text. See examples and fields descriptions below.
- Input MIME type
- application/json
{
"text_input": Explain who you are,
"max_tokens": 128,
"temperature": 0.7,
"top_k": 50,
"top_p": 0.9
}
https://github.com/LG-AI-EXAONE/EXAONE-Examples/blob/main/EXAONE_Text_Generation_AWS_Marketplace.ipynb
Input data descriptions
The following table describes supported input data fields for real-time inference and batch transform.
Field name | Description | Constraints | Required |
|---|---|---|---|
text_input | Prompt text | Type: FreeText | Yes |
max_tokens | number of tokens to generate | Type: Integer
Maximum: 4096 | Yes |
temperature | Sampling Config param: temperature | Default value: 0.7
Type: Continuous | No |
top_k | The number of highest probability vocabulary tokens to keep for top-k-filtering. | Default value: 50
Type: Integer | No |
top_p | If set to < 1, only the smallest set of most probable tokens with probabilities that add up to top_p or higher are kept for generation. | Default value: 1
Type: Continuous | No |
Resources
Support
Vendor support
For inquiries regarding further performance improvement or collaboration for service applications, please contact us via email (contact_us@lgresearch.ai ). For inquiries regarding technical support, please create a new issue in our GitHub repository. https://github.com/LG-AI-EXAONE/EXAONE-ExamplesÂ
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