Sold by: NC
Deployed on AWS
VARCO LLM 2.0 is NC's large language model that can be applied to the development of natural language processing-based AI services.
Overview
VARCO LLM 2.0 is NC's large language model that can be applied to the development of various natural language processing-based AI services such as text generation, question answering, chatbots, summarization, and information extraction. NC's VARCO LLM 2.0 was developed with our own technology, including data construction, pre-training, instruction tuning and alignment tuning. We evaluated VARCO LLM 2.0 on various NLP tasks and its performance has significantly improved compared to VARCO LLM 1.0, and it boasts the highest performance among other Korean LLMs of similar sizes. In particular, it has been trained to be used in high-level natural language processing applications such as creative writing, summarization, question and answering, chatbots and translation, and shows high performance in related quantitative indicators. For inquiries regarding further performance improvement or collaboration for service applications, please contact us by email (varco_llm@ncsoft.com ).
Highlights
- Korean Text Generation : VARCO LLM 2.0 is optimized for Korean natural language generation applications. In particular, it provides more natural and creative responses in understanding user instructions and generating text.
- Key Skills * Question Answering * Summarization * Translation * Text Generation * Chatbots * Information Extraction * Natural Language Understanding * Creative Writing * Instruction Following * Sentiment Analysis
Details
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Delivery method
Latest version
Deployed on AWS
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Pricing
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/host/hour |
|---|---|---|
ml.g4dn.12xlarge Inference (Batch) Recommended | Model inference on the ml.g4dn.12xlarge instance type, batch mode | $0.00 |
ml.g5.12xlarge Inference (Real-Time) Recommended | Model inference on the ml.g5.12xlarge instance type, real-time mode | $1.30 |
Dimensions summary
You pay by the hour based on the machine you run the model on. Two options exist, split by how you process requests. The ml.g4dn.12xlarge option runs in batch mode, where you send groups of requests for processing together. The ml.g5.12xlarge option runs in real-time mode, where the model responds to requests as they arrive. Each option uses a different instance type, so your cost tracks the hours that instance stays active. You pick the instance and mode that fit your workload, then billing scales with your running time.
Top-of-mind questions for buyers
Each option runs on a specific GPU instance type. The batch option uses an ml.g4dn.12xlarge instance. The real-time option uses an ml.g5.12xlarge instance. Your charge tracks the hours that chosen instance stays running. You do not provision separate infrastructure; the model runs on the instance you select.
Batch mode processes groups of requests together, so it suits jobs you can queue and run in bulk. Real-time mode responds to requests as they arrive, so it suits interactive services like chatbots or live Q&A. You pick the mode that matches your request pattern.
Charges accrue per host-hour while your chosen instance runs. A fully stopped instance does not accrue software charges. Underlying AWS storage or other resource fees may still apply separately. The software meter tracks running time only, so cost scales with active hours.
ncsoft.github.io
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Vendor refund policy
Please contact us : varco_llm@ncsoft.com
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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.
Deploy the model on Amazon SageMaker AI using the following options:
Version release notes
Major Version release of VARCO LLM 2.0 BASE from NCSOFT
Additional details
Inputs
- Summary
Model accepts JSON requests. You can check examples and fields descriptions.
- Input MIME type
- application/json
{
"repetition_penalty": 1.0,
"temperature": 0.7,
"top_k": 50,
"top_p": 1.0,
"text": "input text here"
}
https://github.com/ncsoft/ncresearch/blob/feature/VARCO_LLM_2_0/notebooks/train_data_example.json
Input data descriptions
The following table describes supported input data fields for real-time inference and batch transform.
Field name | Description | Constraints | Required |
|---|---|---|---|
repetition_penalty | The parameter for repetition penalty. 1.0 means no penalty.
| Default value: 1.0
Type: Continuous | No |
temperature | The value used to modulate the next token probabilities.
| 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 float < 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: 1.0
Type: Continuous | No |
text | The sequence used as a prompt for the generation or as model inputs to the encoder.
| Type: FreeText | Yes |
Resources
Vendor resources
Support
Vendor support
NC R&D Center, 12, Daewangpangyo-ro 644beon-gil, Bundang-gu, Seongnam-si, Gyeonggi-do, Republic of Korea Tel :02-6201-0099/Email :nc-ai@ncsoft.com
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
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