Sold by: Protopia AI, Inc.Â
Deployed on AWS
Llama-3.1-8B-Instruct with Stained Glass Transform Support, enabled via prompt-embeds support in vLLM.
Overview
Protopia AI's Stained Glass Transform (SGT) is a groundbreaking solution for organizations looking to leverage sensitive data in AI applications with robust security and flexibility. SGT transforms data into unintelligible forms, safeguarding against breaches and minimizing exposure risks without sacrificing fidelity. By enabling full data richness, SGT boosts value derived from AI models. With its low compute overhead, SGT operates efficiently on commodity hardware, freeing up powerful GPUs for critical tasks and offering greater flexibility across on-prem, multi-tenant, and edge environments. SGT's transformation process is fast, with minimal latency, integrating seamlessly into existing AI pipelines to maximize performance and throughput. For custom quotes and offers, please reach out at contact@protopia.aiÂ
Highlights
- Unlock AI Data Potential Securely Access sensitive data without compromising security, enhancing AI model accuracy with high-quality inputs.
- Strengthen AI Security Convert data into unintelligible forms to eliminate exposure risks throughout AI pipelines.
- Stock Llama-3.1-8B-Instruct weights; the model you already know, now with support for protected prompts.
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.g5.4xlarge Inference (Batch) Recommended | Model inference on the ml.g5.4xlarge instance type, batch mode | $0.00 |
ml.g5.4xlarge Inference (Real-Time) Recommended | Model inference on the ml.g5.4xlarge instance type, real-time mode | $0.00 |
ml.m5.xlarge Inference (Batch) | Model inference on the ml.m5.xlarge instance type, batch mode | $0.00 |
ml.m5.4xlarge Inference (Batch) | Model inference on the ml.m5.4xlarge instance type, batch mode | $0.00 |
ml.m5.12xlarge Inference (Batch) | Model inference on the ml.m5.12xlarge instance type, batch mode | $0.00 |
ml.p3.2xlarge Inference (Batch) | Model inference on the ml.p3.2xlarge instance type, batch mode | $0.00 |
ml.g4dn.12xlarge Inference (Batch) | Model inference on the ml.g4dn.12xlarge instance type, batch mode | $0.00 |
ml.g5.2xlarge Inference (Batch) | Model inference on the ml.g5.2xlarge instance type, batch mode | $0.00 |
ml.g5.16xlarge Inference (Batch) | Model inference on the ml.g5.16xlarge instance type, batch mode | $0.00 |
ml.m5.xlarge Inference (Real-Time) | Model inference on the ml.m5.xlarge instance type, real-time mode | $0.00 |
Vendor refund policy
This package is provided free of charge, and no refunds will be provided.
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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
Update manifest to include weights.
Additional details
Inputs
- Summary
Body is fully compatible with OpenAI Chat Completions and Completions request bodies. Note that only Completions-style requests are compatible with prompt embeddings, using vLLM's prompt_embeds key in the JSON body.
- Input MIME type
- application/json, application/jsonlines
{
"messages": [
{"role": "user", "content": "Why is the greenland shark the best shark?"},
],
"max_tokens": 150
}
{"messages": [{"role": "user", "content": "Why is the greenland shark the best shark?"},],"max_tokens": 150},
{"messages": [{"role": "user", "content": "Why is the greenland shark the best shark?"},],"max_tokens": 150},
{"messages": [{"role": "user", "content": "Why is the greenland shark the best shark?"},],"max_tokens": 150}
Resources
Vendor resources
Support
Vendor support
Please contact us for further support at support@protopia.aiÂ
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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Available as a NIM, Llama 3.1 8B-Instruct is an 8B-parameter LLM pretrained, instruction tuned model optimized for multilingual dialogue.
Efficient, fast, and reliable generative AI inference solution of Llama 3.1 8B Instruct Int8 model
![Stained Glass Transform for Llama-3.1-8B-Instruct [Private Offers Only]](https://d7umqicpi7263.cloudfront.net/img/product/9c4e0c3c-fb83-40eb-9ef1-9e15957366fd.com/e7f58fd255573c62cbb35a11559140a0)
Stained Glass Transform (SGT) by Protopia AI allows organizations to securely unlock high-value data for AI applications without compromising privacy. With lightweight, high-speed transformations, SGT strengthens data security, and expands compute options across diverse environments, while retaining model accuracy.
This SGT is specifically to be used with Llama-3.1-8B-Instruct
Please reach out to us at contact@protopia.ai for customized pricing before making a purchase.
This deployment package enables seamless hosting of the meta-llama/Llama-3.1-8B-Instruct language model on Intel® Xeon® processors using the VLLM CPU-optimized Docker image. Designed for efficient inference on CPU-only environments, this solution leverages vLLM lightweight architecture to deliver fast and scalable performance without requiring GPU acceleration. Ideal for enterprise-grade NLP tasks, it offers a cost-effective and accessible way to run large language models on Intel-powered infrastructure.
Llama-3.1-SuperNova-Lite is an 8B parameter model developed by Arcee.ai.
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