Model Overview

Description:

Built with Meta Llama 3 -\nThe Meta Llama 3 family of large language models (LLMs), a collection of pretrained and instruction tuned generative text models in 8 and 70B sizes. The Llama 3 instruction tuned models are optimized for dialogue use cases and outperform many of the available open source chat models on common industry benchmarks. Llama 3 is an auto-regressive language model that uses an optimized transformer architecture.

Terms of use

By accessing this model, you are agreeing to the LLama 3 terms and conditions of the license, acceptable use policy, and Meta’s privacy policy

References(s):

Meta Llama 3 Model Card on Hugging Face
Meta Llama 3 blogpost

Model Architecture:

Architecture Type: Transformer
\nNetwork Architecture: Llama 3
\nModel version: N/A

Input:

Input Format: Text
\nInput Parameters: Temperature, TopP

Output:

Output Format: Text and code\nOutput Parameters: Max output tokens

Software Integration:

Runtime(s): N/A
\nSupported Hardware Platform(s): RTX 4090
\nSupported Operating System(s): Windows

Inference:

TRT-LLM Inference Engine
\nWindows Setup with TRT-LLM

Test Hardware:

RTX 4090

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The Llama 3 instruction tuned models are optimized for dialogue use cases and outperform many of the available open source chat models on common industry benchmarks. Llama 3 is an auto-regressive language model that uses an optimized transformer architecture. \n\n### Terms of use\n\nBy accessing this model, you are agreeing to the LLama 3 terms and conditions of the [license](https://huggingface.co/meta-llama/Meta-Llama-3-8B/blob/main/LICENSE), [acceptable use policy](https://llama.meta.com/llama3/use-policy), and [Meta’s privacy policy](https://www.facebook.com/privacy/policy/)\n\n### References(s):\n\n* Meta Llama 3 [Model Card](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) on Hugging Face \n* Meta Llama 3 [blogpost](https://ai.meta.com/blog/meta-llama-3) \n \n\n### Model Architecture:\n\n**Architecture Type:** Transformer \n**Network Architecture:** Llama 3 \n**Model version:** N/A \n\n### Input:\n\n**Input Format:** Text \n**Input Parameters:** Temperature, TopP \n \n\n### Output:\n\n**Output Format:** Text and code \n**Output Parameters:** Max output tokens \n\n\n### Software Integration:\n\n**Runtime(s):** N/A \n**Supported Hardware Platform(s):** RTX 4090 \n**Supported Operating System(s):** Windows \n\n### Inference:\n\n[TRT-LLM Inference Engine](https://github.com/NVIDIA/TensorRT-LLM/tree/main/examples/llama) \n[Windows Setup with TRT-LLM](https://github.com/NVIDIA/TensorRT-LLM/tree/main/windows) \n\n### Test Hardware:\nRTX 4090","Llama3-8B Instruct Int4",["D",1732745404981],"Meta","/api/image/nvidia/-/models/llama3-8b-instruct","https://catalog.ngc.nvidia.com/demos/llama2.jpg","bias","","explainability","privacy","safetyAndSecurity",[269],[253,254,255],[],[],[],{"_90":265,"_257":266,"_258":267,"_260":261},{"_90":263,"_257":263,"_258":264,"_260":261},{"_90":256,"_257":256,"_258":259,"_260":261},"NSPECT-AA4Q-8OHU","value","filter",{"_262":261,"_257":256},"category","label","field","NSPECT-566U-2ZOY",{"_262":261,"_257":263},"AI","soln_ai",{"_262":268,"_257":266},"technology",{"_90":270,"_257":271,"_258":272,"_260":273},"Runs on RTX","pltfm_runs_on_rtx",{"_262":274,"_257":271},"feature","platform",{"_146":1446,"_148":1447},"ngcApps",[1399],"csaApiBaseUrl","https://www.nvidia.com/ai-agents/csa-agent/dcsm","datadogRum",{"_1380":1381,"_1382":1383,"_1384":1385,"_1386":1387,"_1388":286,"_177":310,"_1389":1390,"_1391":51,"_1392":125,"_1393":125,"_1394":1395,"_1396":125,"_1397":1398},"amplitude",{"_1377":1378,"_983":-7,"_1379":26},"disableJs","environment","prod","featureFlagsBlob","JTdCJTIydGVzdEZsYWclMjIlM0FmYWxzZSUyQyUyMnNob3dTZWFyY2hMYWJlbFNldEZpbHRlcnMlMjIlM0FmYWxzZSUyQyUyMmNoaW5hTmltRGlzdHJpYnV0b3JzUmVkZXNpZ24lMjIlM0F0cnVlJTJDJTIyZW5hYmxlQ3NhV2lkZ2V0JTIyJTNBZmFsc2UlMkMlMjJlbmFibGVQcm9kdWN0R3JvdXBpbmdCeVN1YnNjcmlwdGlvbiUyMiUzQWZhbHNlJTJDJTIyY29udGFpbmVyU2Nhbm5pbmdSZWRlc2lnbk0xJTIyJTNBdHJ1ZSU3RA==","featureFlagsGuarded","isDevLikeEnv","isPlaywright","isMobileDevice","categorizedOrgs",{"_1371":1372,"_1373":1374,"_1375":1376},"currentOrgContext","currentContextRoles",[],"enterpriseOrgs",[],"locale","en","ngcApiOrigin","ngcHelmOrigin","origin","https://catalog.ngc.nvidia.com","usesMocks","theme","year",2026,"1.7.3","defaultSearchSuggestions",{"_1258":244,"_1259":1260,"_1261":1262,"_1263":1264},"announcements",[],"consentState",{"_348":1248,"_1249":125,"_1250":26,"_1251":26,"_1252":1253},"consentConfig",{"_330":331,"_332":333,"_334":335,"_336":337,"_338":339,"_340":341,"_342":343,"_344":345,"_346":347,"_348":349},"showContactAdmin",1784035295145,[],[],[324,325,326,327,328,329],{"_40":54,"_42":65,"_44":141,"_46":-5,"_48":-5,"_50":51},{"_40":54,"_42":63,"_44":141,"_46":-5,"_48":-5,"_50":51},{"_40":54,"_42":61,"_44":141,"_46":-5,"_48":-5,"_50":51},{"_40":54,"_42":59,"_44":141,"_46":-5,"_48":-5,"_50":51},{"_40":52,"_42":53,"_44":141,"_46":-5,"_48":-5,"_50":51},{"_40":41,"_42":43,"_44":141,"_46":-5,"_48":-5,"_50":51},"mainInfoText","We and our third-party partners (including social media, advertising, and analytics partners) use cookies and other tracking technologies to collect, store, monitor, and process certain information about you when you visit our website. 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