Sold by: Arcee
Deployed on AWS
Arcee Nova is a state-of-the-art 72-billion parameter language model developed by Arcee.ai.
Overview
Arcee Nova is a state-of-the-art 72-billion parameter language model developed by Arcee.ai. Its performance approaches that of GPT-4 from May 2023.
Nova is a merge of Qwen2-72B-Instruct with a custom model tuned on a generalist dataset mixture. The model has a 32K maximum context size.
IMPORTANT INFORMATION: Once you have subscribed to the model, we strongly recommend that you deploy it with our sample notebook at https://github.com/arcee-ai/aws-samples/blob/main/model_package_notebooks/sample-notebook-arcee-nova-on-sagemaker.ipynb
Highlights
- Arcee-Nova excels across a wide range of language tasks, demonstrating particular strength in: * Reasoning: Solving complex problems and drawing logical conclusions. * Creative Writing: Generating engaging and original content across various genres. * Coding: Assisting with programming tasks, from code generation to debugging. * General Language Understanding: Comprehending and generating human-like text in diverse contexts.
- Arcee-Nova can be applied to various business tasks: * Customer Service: Implement sophisticated chatbots and virtual assistants. * Content Creation: Generate high-quality written content for marketing and documentation. * Software Development: Accelerate coding processes and improve code quality. * Data Analysis: Enhance data interpretation and generate insightful reports. * Research and Development: Assist in literature reviews and hypothesis generation. * Legal and Compliance: Automate contract analysis and regulatory compliance checks.
Details
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Pricing
This product is available free of charge. Free 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.
Dimensions summary
The software itself is free, so you pay only for the compute instance you run it on. You choose from four options based on the AWS instance type and inference mode. Three run in real-time mode on different GPU instance sizes, letting you match hardware to your workload. The fourth runs in batch mode, which processes grouped requests rather than live responses. Billing is hourly per host (HostHrs), so cost scales with how long you keep an instance running. Pick the instance and mode that fit your performance and cost needs.
Top-of-mind questions for buyers
You are billed hourly per host (HostHrs) only while an instance runs. Since the software is free, stopping an instance ends software charges. Underlying AWS compute and storage fees may still apply based on your AWS account settings. Shut down instances you are not using to control cost.
Real-time mode processes live requests as they arrive, so you keep an instance running for immediate responses. Batch mode groups requests and processes them together, which suits large jobs without a need for instant replies. Both bill hourly per host, but batch runs on the ml.p3.16xlarge instance.
The model handles language tasks like reasoning, creative writing, coding help, and general text understanding. Business uses include chatbots, content creation, code assistance, data interpretation, and document analysis. You choose the instance size and mode to match your workload's speed and volume needs.
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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
This model package is configured for p4 and p5 8-GPU instances. Context size is 32 KB and the OpenAI Messages API is enabled.
Additional details
Inputs
- Summary
You can invoke the model withr the OpenAI Messages AI. Please see the sample notebook for details.
- Input MIME type
- application/json, application/jsonlines
{
"messages": [
{
"role": "system",
"content": "As a friendly technical assistant engineer, answer the question in detail.",
},
{"role": "user", "content": "Why are transformers better models than LSTM?"},
],
"max_tokens": 256
}
https://github.com/arcee-ai/aws-samples/blob/main/model_package_notebooks/sample-notebook-arcee-nova-on-sagemaker.ipynb
Input data descriptions
The following table describes supported input data fields for real-time inference and batch transform.
Field name | Description | Constraints | Required |
|---|---|---|---|
OpenAI Messages API | Please see sample notebook. | Type: FreeText | Yes |
Resources
Vendor resources
Support
Vendor support
IMPORTANT INFORMATION: Once you have subscribed to the model, we strongly recommend that you deploy it with our sample notebook at https://github.com/arcee-ai/aws-samples/blob/main/model_package_notebooks/sample-notebook-arcee-nova-on-sagemaker.ipynb . This is the only way to guarantee proper configuration and optimization. Due to the size of the model, deploying through the marketplace (e.g., with CloudFormation) may not work correctly and face download timeouts.
Bugs, questions, feature requests: please create an issue in the aws-samples repository on Github.
Contact: julien@arcee.ai
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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