Llama-3.1-8B-Instruct

Description:

This container houses the Llama-3.1-8B-Instruct, which is an 8 billion parameter, instruction-tuned large language model created by Meta. This model is part of the Llama 3.1 family of open-access models and is specifically optimized for dialogue and conversational use cases, making it highly capable of following user instructions to perform a wide variety of natural language processing tasks.

The container components are ready for commercial/non-commercial use.

Documentation

Visit the NIM Container LLM page for release documentation, deployment guides, and more.

Third-Party Community Consideration

This model is not owned or developed by NVIDIA. This model has been developed and built to a third-party's requirements for this application and use case; see link to Non-NVIDIA [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct).

License/Terms of Use:

GOVERNING TERMS: The NIM container is governed by the NVIDIA Software License Agreement and the Product-Specific Terms for AI Products.

The use of any models in this container is governed by the NVIDIA Open Model Agreement in addition to any terms which govern the specific models used.

You are responsible for ensuring that your use of any provided models complies with all applicable laws.

Use of this model is governed by the NVIDIA Open Model Agreement. The underlying model is also licensed under the Llama 3.1 Community License Agreement. Built with Llama.

Deployment Geography:

Global

Release Date:

Build.NVIDIA.com 07/23/2024 via
\nhttps://build.nvidia.com/meta/llama-3_1-8b-instruct

Huggingface 07/23/2024 via
\nhttps://huggingface.co/meta-llama/Llama-3.1-8B-Instruct

Program Classes

Llama-3.1-8B-Instruct Container includes the following model:

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n

tr:nth-child(odd)]:bg-surface-sunken\">

Model Name & Link	Use Case	How to Pull the Model
Llama-3.1-8B-Instruct	A conversational AI model for instruction-following, content generation, summarization, and coding assistance.	Automatic

Deployment Details:

Our AI models are designed and/or optimized to run on NVIDIA GPU-accelerated systems. By leveraging NVIDIA’s hardware (e.g. GPU cores) and software frameworks (e.g., CUDA libraries), the model achieves faster training and inference times compared to CPU-only solutions.

Security Common Vulnerabilities and Exposures (CVEs)

Please review the Security Scanning tab on NGC to view the latest security scan results.\nFor certain open-source vulnerabilities listed in the scan results, NVIDIA provides a response in the form of a Vulnerability Exploitability eXchange (VEX) document. The VEX information can be reviewed and downloaded from the Security Scanning tab.

Ethical Considerations:

NVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their internal developer team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse.

Please report quality, risk, security vulnerabilities or NVIDIA AI Concerns here.

Get Help

NVIDIA Developer Community Forum

Get access to community knowledge base articles and support cases (https://forums.developer.nvidia.com/)

Enterprise Support

Get access to knowledge base articles and support cases or submit a ticket.

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(2.0.8)","nim/meta/llama-3.1-8b-instruct","nim/meta/containers/llama-3.1-8b-instruct","llama-3.1-8b-instruct","NVIDIA NIM for GPU accelerated Llama-3.1-8B-Instruct inference through OpenAI compatible APIs","# **Llama-3.1-8B-Instruct**\n\n## **Description:**\n\nThis container houses the **Llama-3.1-8B-Instruct**, which is an 8 billion parameter, instruction-tuned large language model created by Meta. This model is part of the Llama 3.1 family of open-access models and is specifically optimized for dialogue and conversational use cases, making it highly capable of following user instructions to perform a wide variety of natural language processing tasks.\n\nThe container components are ready for commercial/non-commercial use.\n\n**Documentation**\n\nVisit the [NIM Container LLM](https://docs.nvidia.com/nim/large-language-models/latest/introduction.html) page for release documentation, deployment guides, and more.\n\n\n## **Third-Party Community Consideration**\n\nThis model is not owned or developed by NVIDIA. This model has been developed and built to a third-party's requirements for this application and use case; see link to Non-NVIDIA \\[meta-llama/Llama-3.1-8B-Instruct\\](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct). \n\n## **License/Terms of Use:**\n\n**GOVERNING TERMS:** The NIM container is governed by the [NVIDIA Software License Agreement](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-software-license-agreement/) and the [Product-Specific Terms for AI Products](https://www.nvidia.com/en-us/agreements/enterprise-software/product-specific-terms-for-ai-products/).\n\nThe use of any models in this container is governed by the [NVIDIA Open Model Agreement](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-agreement/) in addition to any terms which govern the specific models used.\n\nYou are responsible for ensuring that your use of any provided models complies with all applicable laws.\n\nUse of this model is governed by the [NVIDIA Open Model Agreement](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-agreement/). The underlying model is also licensed under the [Llama 3.1 Community License Agreement](https://www.llama.com/llama3_1/license/). Built with Llama.\n\n\n## **Deployment Geography:**\n\nGlobal \n\n## **Release Date:**\n\nBuild.NVIDIA.com 07/23/2024 via \n[https://build.nvidia.com/meta/llama-3_1-8b-instruct](https://build.nvidia.com/meta/llama-3_1-8b-instruct)\n\nHuggingface 07/23/2024 via \n[https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct)\n\n## Program Classes\n\nLlama-3.1-8B-Instruct Container includes the following model:\n\n| Model Name & Link | Use Case | How to Pull the Model |\n| :---- | :---- | :---- |\n| [Llama-3.1-8B-Instruct](https://catalog.ngc.nvidia.com/orgs/nim/teams/meta/models/llama-3.1-8b-instruct) | A conversational AI model for instruction-following, content generation, summarization, and coding assistance. | Automatic |\n\n## **Deployment Details:**\n\nOur AI models are designed and/or optimized to run on NVIDIA GPU-accelerated systems. By leveraging NVIDIA’s hardware (e.g. GPU cores) and software frameworks (e.g., CUDA libraries), the model achieves faster training and inference times compared to CPU-only solutions.\n\n## Security Common Vulnerabilities and Exposures (CVEs)\nPlease review the Security Scanning tab on NGC to view the latest security scan results.\nFor certain open-source vulnerabilities listed in the scan results, NVIDIA provides a response in the form of a Vulnerability Exploitability eXchange (VEX) document. The VEX information can be reviewed and downloaded from the Security Scanning tab.\n\n## **Ethical Considerations:**\n\nNVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their internal developer team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse.\n\nPlease report quality, risk, security vulnerabilities or NVIDIA AI Concerns [here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/).\n\n## **Get Help**\n\n### NVIDIA Developer Community Forum\nGet access to community knowledge base articles and support cases (https://forums.developer.nvidia.com/)\n\n### Enterprise Support\nGet access to knowledge base articles and support cases or [submit a ticket](https://www.nvidia.com/en-us/data-center/products/ai-enterprise-suite/support/).","Llama-3.1-8B-Instruct",["D",1783628245071],[359,357,355,353,351,349,347,207,342,338,344,334,332,326,324,330,328,340,361,322,318,316,314,320,312,310,308,306,304,302,300,296,298,294],"/api/image/nim/meta/containers/llama-3.1-8b-instruct",12526373888,{"_414":415,"_416":417,"_418":419,"_420":26,"_421":422},"hasSignedTag",[405,406],[389,390,391,392,393],[],[382,383],[],{"_91":387,"_141":387,"_142":388,"_144":386},{"_91":384,"_141":384,"_142":385,"_144":386},"signed images",{"_146":386,"_141":384},"system","Elastic NIM",{"_146":386,"_141":387},{"_91":92,"_141":402,"_142":403,"_144":145},{"_91":400,"_141":400,"_142":401,"_144":145},{"_91":398,"_141":398,"_142":399,"_144":145},{"_91":396,"_141":396,"_142":397,"_144":145},{"_91":394,"_141":394,"_142":395,"_144":145},"NSPECT-ZP6P-5LPY",{"_146":145,"_141":394},"NIM",{"_146":145,"_141":396},"Llama3.1-8b-instruct",{"_146":145,"_141":398},"Llama3.1",{"_146":145,"_141":400},"gpu_type_dgx_spark",{"_146":404,"_141":402},"gpuType",{"_91":412,"_141":412,"_142":413,"_144":410},{"_91":407,"_141":408,"_142":409,"_144":410},"NVIDIA NIM","nimmcro_nvidia_nim",{"_146":411,"_141":408},"feature","nvidia_nim","NVIDIA AI Enterprise Supported",{"_146":145,"_141":412},"governingTerms","

GOVERNING DOWNLOAD TERMS:

The NIM container is governed by the NVIDIA Software License Agreement (https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-software-license-agreement/) and the Product-Specific Terms for AI Products (https://www.nvidia.com/en-us/agreements/enterprise-software/product-specific-terms-for-ai-products/).

The use of any models in this container is governed by the NVIDIA Open Model License Agreement (found at https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-license/) in addition to any terms which govern the specific models used.

You are responsible for ensuring that your use of any provided models complies with all applicable laws.

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It is used as a URL shortening service, which allows Twitter to collect data on how links are shared.","snowplow.com",[586],{"_123":587,"_553":584,"_554":26,"_90":588},"sp","Testing","google.com",[591],{"_123":592,"_553":589,"_554":26,"_90":593},"NID","This domain is owned by Google Inc. Although Google is primarily known as a search engine, the company provides a diverse range of products and services. Its main source of revenue however is advertising. Google tracks users extensively both through its own products and sites, and the numerous technologies embedded into many millions of websites around the world. It uses the data gathered from most of these services to profile the interests of web users and sell advertising space to organisations based on such interest profiles as well as aligning adverts to the content on the pages where its customer's adverts appear.","tags.srv.stackadapt.com",[596,597,598,599],{"_123":604,"_553":594,"_554":26,"_90":601},{"_123":603,"_553":594,"_554":26,"_90":601},{"_123":602,"_553":594,"_554":26,"_90":601},{"_123":600,"_553":594,"_554":26,"_90":601},"sa-user-id-v3","This domain is associated with StackAdapt, a platform for programmatic advertising, which suggests that it is used for targeting and advertising purposes.","sa-user-id","sa-user-id-v2","sa-user-id-v4","linkedin.com",[607],{"_123":608,"_553":605,"_554":26,"_90":609},"bcookie","This domain is owned by LinkedIn, the business networking platform. 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Where twitter acts as a third party host, it collects data through a range of plug-ins and integrations, that is primarily used for tracking and targeting.","guest_id_marketing","guest_id","Twitter does not currently provide information on the use of specific cookies.","guest_id_ads","youtube.com",[624,625,626,627],{"_123":633,"_553":622,"_554":26,"_90":631},{"_123":632,"_553":622,"_554":26,"_90":631},{"_123":630,"_553":622,"_554":26,"_90":631},{"_123":628,"_553":622,"_554":26,"_90":629},"VISITOR_INFO1_LIVE","This cookie is used as a unique identifier to track viewing of videos","__Secure-YNID","YouTube is a Google owned platform for hosting and sharing videos. 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It stores a unique visitor identifier, and uses an organisation identifier to allow a company to track users across their domains and services.This is a pattern type cookie name associated with Adobe Marketing Cloud. It stores a unique visitor identifier, and uses an organisation identifier.","kndctr_F207D74D549850760A4C98C6_AdobeOrg_identity","_rdt_pn","www.nvidia.com","This cookie name is associated with www.mind.org.uk which is used for marketing purposes.","ai-podcast.nvidia.com","This cookie is used to identify the user's session on the website and is often associated with analytics or personalization.","_gcl_au","Used by Google AdSense for experimenting with advertisement efficiency across websites using their services","_mkto_trk","This cookie is associated with an email marketing service provided by Marketo. This tracking cookie allows a website to link visitor behaviour to the recipient of an email marketing campaign, to measure campaign effectiveness.","_gat_gtag_UA_140825383_2","Google Analytics","_zitok","This cookie name is associated with ZoomInfo which is used to maintain a unique visitor identifier and store Personally Identifiable Information.","_rdt_uuid","This cookie is set by Reddit and is used for tracking the views of embedded videos and performance of the advertisements.","AMP_91bf70adfe","Supports Amplitude product analytics.","This cookie name is associated with StackAdapt Inc. which is used to support the effective management and optimization of digital advertising campaigns by handling information such as visitor actions on websites, visited pages, time spent, page load speed, and more.","build.nvidia.com","kndctr_F207D74D549850760A4C98C6_AdobeOrg_cluster","_cs_nnnnnnnnnnnnn","This is a session cookie. 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It is commonly used for analytics and personalization of content.","marketplace.nvidia.com","AMP_MKTG_92dea1e784","This cookie is typically associated with SnackTools, which is a suite of web applications for creating and sharing multimedia content. It is used to identify a user across sessions and track user activities.","forums.developer.nvidia.com","This cookie is typically associated with the use of Taptap Digital, a company specializing in digital advertising. It is used for tracking and ad personalization purposes.","_tt_enable_cookie","This cookie name is associated with TikTok which is used to collect data about behavior and purchases on the website and to measure the effect of advertising. It is also used to track website activity to help optimize advertising efforts.","AMCV_xxxxxAdobeOrg","This cookie is used to identify a unique visitor for tracking purposes by Adobe Experience Cloud.This is a pattern type cookie name associated with Adobe Marketing Cloud. It stores a unique visitor identifier, and uses an organisation identifier to allow a company to track users across their domains and services.","ttcsid","This cookie name is associated with TikTok which is used to enable TikTok Ads session tracking by assigning a unique session ID to users who click on TikTok ads, allowing for the attribution of user behavior and conversions within the same session.This cookie is associated with TikTok. It helps track your activity on the platform, including how you interact with their embedded services on other websites.","AMP_MKTG_91bf70adfe","C0003","Personalization Cookies","These cookies collect data about how you have interacted with our website to help us improve your web experience, such as which pages you have visited. These cookies may store a unique ID so that our system will remember you when you return. They may be set by us or by third party providers whose services we have added to our pages. These cookies enable us to provide enhanced website functionality and personalization as well as make the marketing messages we send to you more relevant to your interests. If you do not allow these cookies, then some or all of these services may not function properly.",4,[780,781,782,783,784,785,786,787,788,789,790,791,792,793,794,795,796,797,798,799,800],[745,746,747,748,749],{"_547":639,"_91":639,"_90":104,"_521":771},{"_547":605,"_91":605,"_90":104,"_521":766},{"_547":759,"_91":759,"_90":104,"_521":760},{"_547":755,"_91":755,"_90":104,"_521":756},{"_547":750,"_91":750,"_90":104,"_521":751},"nvcrm.my.site.com",[752],{"_123":753,"_553":750,"_554":26,"_90":754},"BrowserId","If you know anything about this cookie and its uses that are not specific to a particular site please add your contributions.","nvidia.partners",[757],{"_123":758,"_553":755,"_554":26,"_90":588},"edge","github.com",[761,762],{"_123":765,"_553":759,"_554":26,"_90":764},{"_123":763,"_553":759,"_554":26,"_90":764},"logged_in","This domain is owned by Github. 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The data is aggregated and analyzed; therefore, it remains anonymous upon use.\n","nvHeadless","This cookie is likely used to track if a user is using the site in a 'headless' non-GUI mode, which could be for accessibility reasons or for automated processes.","_biz_nA","C0002","Performance Cookies","These cookies are used to provide quantitative measures of our website visitors, such as the number of times you visit, time on page, your mouse movements, scrolling, clicks and keystroke activity on the websites; other browsing, search, or product research behavior; and what brought you to our site. These cookies may store a unique ID so that our system will remember you when you return. Information collected with these cookies is used to measure and find ways to improve website 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