Amazon Sagemaker
Amazon SageMaker is a fully-managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale. With Amazon SageMaker, all the barriers and complexity that typically slow down developers who want to use machine learning are removed. The service includes models that can be used together or independently to build, train, and deploy your machine learning models.
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Stable Diffusion XL Beta 0.8
By:
Latest Version:
1.0
The early beta for Stability AI’s foundation model for image generation, targeting medium resolution (512px) for fast image generation.
Product Overview
Stable Diffusion XL Beta 0.8 is the first public release of the evolution of the Stable Diffusion series of models. Calibrated for 512px native image generation at square aspect ratios, SDXL Beta 0.8 is capable of enhanced image composition targeting a variety of realistic and artistic stiles.
Key Data
Version
Type
Model Package
Highlights
A new era in image generation: The largest image generation model to date and the first based on a new SDXL architecture, using 3.1B parameters to enable next-level photorealism and legible text even from simple prompts
A preview of the new foundation model for images: SDXL Beta 0.8 is an intermediate step from the older, faster Stable Diffusion series, and the more powerful SDXL series. This version is useful for those who do not need the highest quality and flexibility, but still want to upgrade from SD 1.X or 2.X
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Pricing Information
Use this tool to estimate the software and infrastructure costs based your configuration choices. Your usage and costs might be different from this estimate. They will be reflected on your monthly AWS billing reports.
Estimating your costs
Choose your region and launch option to see the pricing details. Then, modify the estimated price by choosing different instance types.
Version
Region
Software Pricing
Model Realtime Inference$0.00/inference
running on any instance
Model Batch Transform$0.00/hr
running on ml.g4dn.12xlarge
Infrastructure PricingWith Amazon SageMaker, you pay only for what you use. Training and inference is billed by the second, with no minimum fees and no upfront commitments. Pricing within Amazon SageMaker is broken down by on-demand ML instances, ML storage, and fees for data processing in notebooks and inference instances.
Learn more about SageMaker pricing
With Amazon SageMaker, you pay only for what you use. Training and inference is billed by the second, with no minimum fees and no upfront commitments. Pricing within Amazon SageMaker is broken down by on-demand ML instances, ML storage, and fees for data processing in notebooks and inference instances.
Learn more about SageMaker pricing
SageMaker Realtime Inference$1.408/host/hr
running on ml.g5.xlarge
SageMaker Batch Transform$4.89/host/hr
running on ml.g4dn.12xlarge
Model Realtime Inference
For model deployment as Real-time endpoint in Amazon SageMaker, the software is priced based on the number of inferences generated by the ML Model per month. Typically, the number of inferences is the same as the number of successful calls to the real-time endpoint. For models that support multiple inputs in a request, sellers have the option to meter the number of inputs processed in a request to count generated inferences.
Additional infrastructure cost, taxes or fees may apply.
Usage Information
Model input and output details
Input
Summary
This model accepts JSON input aligned with the Stability REST API as well as protocol buffers aligned with the Stability GRPC API . You can also use the Stability SDK to deploy and interact with the model.
Limitations for input type
Input images must be base64 encoded in JSON or supplied via protobuf.
Input MIME type
application/jsonSample input data
{
"cfg_scale": 7,
"height": 512,
"width": 512,
"steps": 50,
"seed": 42,
"text_prompts": [
{
"text": "A photograph of fresh pizza with basil and tomatoes, from a traditional oven",
"weight": 1
}
]
}
Output
Summary
Model output is available as base64 inside JSON, binary serialized protocol buffers, or binary PNG
Output MIME type
image/png, application/jsonSample output data
{
"result": "success",
"artifacts": [
{
"base64": "...very long string...",
"finishReason": "SUCCESS",
"seed": 1050625087
},
{
"base64": "...very long string...",
"finishReason": "CONTENT_FILTERED",
"seed": 1229191277
}
]
}
Sample notebook
Additional Resources
End User License Agreement
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Support Information
AWS Infrastructure
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.
Learn MoreRefund Policy
This product is offered for free. If there are any questions, please contact us for further clarifications.
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