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This content handler is then passed when invoking the model, in addition to the aforementioned hyperparameters and custom attributes (EULA acceptance). You should select your hyperparameters based on your use case and test them appropriately. The system prompt informs the model of its role in assisting the user for a particular use case.

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Code Llama 70B is now available in Amazon SageMaker JumpStart

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Accept the End User License Agreement (EULA) and choose Deploy. You can find more information about the model on the Code Llama 70B model card. The following screenshot shows the endpoint settings. You can change the options or use the default ones. This will start the endpoint deployment process, as shown in the following screenshot.

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AI21 Jurassic-1 foundation model is now available on Amazon SageMaker

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NOVEMBER 30, 2022

Read through the EULA for the model before proceeding. Evaluate the Jurassic-1 Grande model with a test widget. On the Jurassic-1 Grande listing, choose View Model. You will see a description of the model and the tasks that you can perform. Let’s first try out the model for text summarization. Choose Try out model.

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Databricks DBRX is now available in Amazon SageMaker JumpStart

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The Eula value must be explicitly defined as True in order to accept the end-user license agreement (EULA). Similarly, you can deploy DBRX Instruct using its own model ID. You can change these configurations by specifying non-default values in JumpStartModel. Also make sure you have the account-level service limit for using ml.p4d.24xlarge

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Code Llama code generation models from Meta are now available via Amazon SageMaker JumpStart

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OCTOBER 2, 2023

Customers must accept the EULA to deploy model visa SageMaker SDK. Custom_attributes used to pass EULA are key/value pairs. The model is deployed in an AWS secure environment and under your VPC controls, helping ensure data security. Code Llama models are discoverable and can be deployed in in US East (N.

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Solar models from Upstage are now available in Amazon SageMaker JumpStart

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If you have not subscribed to this model, choose Subscribe , go to AWS Marketplace, review the pricing terms and End User License Agreement (EULA), and choose Accept offer. If you have already subscribed to this model, and have been approved to use the product, you can deploy the model directly.

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Gemma is now available in Amazon SageMaker JumpStart

AWS Machine Learning

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from sagemaker.jumpstart.model import JumpStartModel model = JumpStartModel(model_id=model_id, model_version=model_version) predictor= model.deploy(accept_eula=False) # manually accept EULA here! The deployment might take 5-10 minutes.

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Benchmark and optimize endpoint deployment in Amazon SageMaker JumpStart

AWS Machine Learning

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.*", instance_type="ml.g5.12xlarge", env={ "MAX_CONCURRENT_REQUESTS": "1", "MAX_INPUT_TOKENS": "256", "MAX_TOTAL_TOKENS": "512", }, ) predictor = model.deploy(accept_eula=False) # Change EULA acceptance to True Note that the latency numbers change depending on the number of input and output tokens.

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Llama Guard is now available in Amazon SageMaker JumpStart

AWS Machine Learning

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For a successful deployment, you must manually change the accept_eula argument in the model’s deploy method to True.

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Use Stable Diffusion XL with Amazon SageMaker JumpStart in Amazon SageMaker Studio

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On the Subscribe to this software page, review the pricing details and End User Licensing Agreement (EULA). Many enterprises may limit AWS Marketplace permissions to control the actions that someone can take in the AWS Marketplace Management Portal. Choose Continue to Subscribe. If agreeable, choose Accept offer. Choose a supported Region.

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Accelerate your learning towards AWS Certification exams with automated quiz generation using Amazon SageMaker foundations models

AWS Machine Learning

MAY 31, 2023

Read through the EULA for the model before proceeding. Evaluate the Jurassic-2 Jumbo Instruct model in the model playground On the AI21 Jurassic-2 Jumbo Instruct listing, choose View Model. You will see a description of the model and the tasks that you can perform. Navigate to the Playground tab.

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AWS Machine Learning

JUNE 27, 2023

On the Subscribe to this software page , review the details and choose Accept offer if you and your organization agree with the EULA, pricing, and support terms. Many enterprises may limit AWS Marketplace permissions to control the actions that someone with those permissions can take in the AWS Marketplace Management Portal.

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Alida gains deeper understanding of customer feedback with Amazon Bedrock

AWS Machine Learning

MARCH 4, 2024

On the Model access page, review the EULA and enable the FMs you’d like in your account. You can get started with the following steps: Verify that your user or role has permission to create or modify Amazon Bedrock resources. For details, see Identity-based policy examples for Amazon Bedrock Log in into the Amazon Bedrock console.

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Llama 2 foundation models from Meta are now available in Amazon SageMaker JumpStart

AWS Machine Learning

JULY 18, 2023

Custom_attributes used to pass EULA are key/value pairs. By doing so, you accept the user license agreement and acceptable use policy as mentioned earlier. You can also download the license agreement. in this case, used for conditional logic).

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Create a Generative AI Gateway to allow secure and compliant consumption of foundation models

AWS Machine Learning

SEPTEMBER 28, 2023

For example, handling hallucinations, managing company-specific IPs and EULAs (End User License Agreements), as well as moderating generations are new responsibilities that go beyond the scope of traditional API Gateways.

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Package and deploy classical ML and LLMs easily with Amazon SageMaker, part 2: Interactive User Experiences in SageMaker Studio

AWS Machine Learning

NOVEMBER 30, 2023

Note that use of LLMs is subject to EULA and the terms and conditions of the provider. Choose one of the partner names to browse the list of models available from that partner, or use the search feature to get to the model page if you know the name of the model. Choose the model you want to deploy. Choose Deploy. Accept the license and terms.

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Fine-tune Llama 2 for text generation on Amazon SageMaker JumpStart

AWS Machine Learning

SEPTEMBER 6, 2023

To use Llama 2 models, you need to accept the End User License Agreement (EULA). Choose I have read and accept EULA and AUP to start the fine-tuning job. It will show up when you when you choose Train , as shown in the following screenshot.

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Fine-tune and deploy Llama 2 models cost-effectively in Amazon SageMaker JumpStart with AWS Inferentia and AWS Trainium

AWS Machine Learning

JANUARY 17, 2024

Setting this argument to be true, acknowledges you have read and accepted the EULA of the model. The EULA can be found in the model card description or from the Meta website. To use Llama 2 models, you need to accept the EULA and AUP. Choose I have read and accept EULA and AUP to start the fine-tuning job.

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Build knowledge-powered conversational applications using LlamaIndex and Llama 2-Chat

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