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Running multi agents on open source models has always been a hit or miss until... Llama 3.1 on GroqInc with 405b and 70b

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FlowiseAI

29,234 subscribers

48,225 просмотров • 2 лет назад •via X (Twitter)

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Комментарии: 10

Фото профиля Matheus Castelo | NoCode Dev 👨‍💻
Matheus Castelo | NoCode Dev 👨‍💻2 лет назад

@GroqInc @netocamarano

Фото профиля Alexander De Ridder
Alexander De Ridder2 лет назад

@GroqInc Sounds like Llama 3.1 is setting a new standard in multi-agent systems. What specific features are you most excited about? 🚀

Фото профиля Stickmannn
Stickmannn2 лет назад

@GroqInc Hey, how do I update the flowise I think I am using some older version :

Фото профиля FlowiseAI
FlowiseAI2 лет назад

@ryanjohn153 @GroqInc depending on how you are running Flowise, normally you sync your forked repo, then redeploy. If using Docker, git pull the latest, and start again.

Фото профиля Stickmannn
Stickmannn2 лет назад

@GroqInc @FlowiseAI I installed using "npm install -g flowise" cmd on debian

Фото профиля FlowiseAI
FlowiseAI2 лет назад

@ryanjohn153 @GroqInc You just need to reinstall again, that will update to latest version

Фото профиля Stickmannn
Stickmannn2 лет назад

@GroqInc @FlowiseAI Does it delete my previous data

Фото профиля FlowiseAI
FlowiseAI2 лет назад

@ryanjohn153 @GroqInc not if you have persisted your data - in this case, I recommend hopping on to our cloud waitlist so you dont need to worry about all these anymore

Фото профиля AImaster
AImaster2 лет назад

@GroqInc where can I get or access this agents software?

Фото профиля FlowiseAI
FlowiseAI2 лет назад

@GroqInc or

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Running Llama 3.1 locally as a code assistant in VSCode with ollama ✨ Download Ollama ( ✨ Download CodeGPT ( ✨ Select the Llama 3.1 model (8b, 70b or 405b) ✨ Click download ✨ Enjoy! :)
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Running Llama 3.1 locally as a code assistant in VSCode with ollama ✨ Download Ollama ( ✨ Download CodeGPT ( ✨ Select the Llama 3.1 model (8b, 70b or 405b) ✨ Click download ✨ Enjoy! :)

Daniel San

359,980 просмотров • 2 лет назад

With today’s launch of our Llama 3.1 collection of models we’re making history with the largest and most capable open source AI model ever released. 128K context length, multilingual support, and new safety tools. Download 405B and our improved 8B & 70B here.
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With today’s launch of our Llama 3.1 collection of models we’re making history with the largest and most capable open source AI model ever released. 128K context length, multilingual support, and new safety tools. Download 405B and our improved 8B & 70B here.

Ahmad Al-Dahle

867,185 просмотров • 2 лет назад

Introducing LlamaCoder! An open source Claude Artifacts app that can generate full React apps and components with Llama 3.1 405B. 100% free and open source.
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Introducing LlamaCoder! An open source Claude Artifacts app that can generate full React apps and components with Llama 3.1 405B. 100% free and open source.

Hassan

501,759 просмотров • 2 лет назад

With the release of Llama 3.1 405B, @TogetherCompute built LlamaCoder — an open source web app that can generate an entire app from a prompt. The repo has now been cloned by hundreds of devs on GitHub and starred 2K+ times. More on this project ➡️
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With the release of Llama 3.1 405B, @TogetherCompute built LlamaCoder — an open source web app that can generate an entire app from a prompt. The repo has now been cloned by hundreds of devs on GitHub and starred 2K+ times. More on this project ➡️

AI at Meta

260,695 просмотров • 2 лет назад

Starting today, open source is leading the way. Introducing Llama 3.1: Our most capable models yet. Today we’re releasing a collection of new Llama 3.1 models including our long awaited 405B. These models deliver improved reasoning capabilities, a larger 128K token context window and improved support for 8 languages among other improvements. Llama 3.1 405B rivals leading closed source models on state-of-the-art capabilities across a range of tasks in general knowledge, steerability, math, tool use and multilingual translation. The models are available to download now directly from Meta or Hugging Face. With today’s release the ecosystem is also ready to go with 25+ partners rolling out our latest models — including Amazon Web Services, NVIDIA, Databricks, GroqInc, Dell Technologies, Microsoft Azure and Google Cloud ready on day one. More details in the full announcement ➡️ Download Llama 3.1 models ➡️ With these releases we’re setting the stage for unprecedented new opportunities and we can’t wait to see the innovation our newest models will unlock across all levels of the AI community.
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Starting today, open source is leading the way. Introducing Llama 3.1: Our most capable models yet. Today we’re releasing a collection of new Llama 3.1 models including our long awaited 405B. These models deliver improved reasoning capabilities, a larger 128K token context window and improved support for 8 languages among other improvements. Llama 3.1 405B rivals leading closed source models on state-of-the-art capabilities across a range of tasks in general knowledge, steerability, math, tool use and multilingual translation. The models are available to download now directly from Meta or Hugging Face. With today’s release the ecosystem is also ready to go with 25+ partners rolling out our latest models — including Amazon Web Services, NVIDIA, Databricks, GroqInc, Dell Technologies, Microsoft Azure and Google Cloud ready on day one. More details in the full announcement ➡️ Download Llama 3.1 models ➡️ With these releases we’re setting the stage for unprecedented new opportunities and we can’t wait to see the innovation our newest models will unlock across all levels of the AI community.

AI at Meta

1,270,202 просмотров • 2 лет назад

Very, very fast voice bots. Llama 3.1 running on GroqInc. 🚀 500ms voice-to-voice response times
1:52

Very, very fast voice bots. Llama 3.1 running on GroqInc. 🚀 500ms voice-to-voice response times

kwindla

386,589 просмотров • 2 лет назад

Introducing `llama-405b-to-8b` ✍️ Get the quality of Llama 3.1 405B, at a fraction of the cost and latency. Give one example of your task, and 405B will teach 8B (~30x cheaper!!) how to do the task perfectly. And it's open-source:
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Introducing `llama-405b-to-8b` ✍️ Get the quality of Llama 3.1 405B, at a fraction of the cost and latency. Give one example of your task, and 405B will teach 8B (~30x cheaper!!) how to do the task perfectly. And it's open-source:

Matt Shumer

278,444 просмотров • 2 лет назад

Llama 3.3 70B 4-bit running on a 128GB M4 Max with MLX LM (~12 toks/sec) with mactop on the right. "Good enough", local, private and open models are now more accessible than ever!
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Llama 3.3 70B 4-bit running on a 128GB M4 Max with MLX LM (~12 toks/sec) with mactop on the right. "Good enough", local, private and open models are now more accessible than ever!

Ivan Fioravanti ᯅ

43,937 просмотров • 1 год назад

This is the fastest I've seen Llama 3.3 running anywhere! Llama 3.3 70B running at 652 t/s is lightning fast. And if you want Llama 3.1, here are the speeds I was able to get: • Llama 3.1 8B: 1006 t/s • Llama 3.1 70B: 709 t/s • Llama 3.1 405B: 206 t/s (You can access all of these models for free! See the link below.) This speed is incredible, but the interesting part is what's happening behind the scenes: These models aren't running on a GPU! In this video, I'm using the SambaNova cloud to access these models. They built a custom chip (SN40L) optimized for AI workflows. A single SN40L chip can hold hundreds of models (trillions of parameters) in memory! The speed alone is a huge deal, but the big advantage is for agentic workflows running multiple specialized models. A GPU can only host a single model and switch (unload and load) to a different model if necessary. An SN40L, on the other hand, can host every model at once, making it much faster. Here is the video where you can see how fast these chips are:
7:24

This is the fastest I've seen Llama 3.3 running anywhere! Llama 3.3 70B running at 652 t/s is lightning fast. And if you want Llama 3.1, here are the speeds I was able to get: • Llama 3.1 8B: 1006 t/s • Llama 3.1 70B: 709 t/s • Llama 3.1 405B: 206 t/s (You can access all of these models for free! See the link below.) This speed is incredible, but the interesting part is what's happening behind the scenes: These models aren't running on a GPU! In this video, I'm using the SambaNova cloud to access these models. They built a custom chip (SN40L) optimized for AI workflows. A single SN40L chip can hold hundreds of models (trillions of parameters) in memory! The speed alone is a huge deal, but the big advantage is for agentic workflows running multiple specialized models. A GPU can only host a single model and switch (unload and load) to a different model if necessary. An SN40L, on the other hand, can host every model at once, making it much faster. Here is the video where you can see how fast these chips are:

Santiago

97,561 просмотров • 1 год назад

Exclusive: Meta just released Llama 3.1 405B — the first-ever open-sourced frontier AI model, beating top closed models like GPT-4o across several benchmarks. I sat down with Mark Zuckerberg, diving into why this marks a major moment in AI history. Timestamps: 00:00 Intro 00:38 Meta’s Llama 3.1 rundown 03:44 Real-world use cases for Llama 3.1 06:15 Educating developers on open-source AI tools 09:43 Societal implications of open-source AI 13:00 Balancing power and managing bad actors 14:40 Open source and global competition 16:59 Accelerating innovation and economic growth 20:04 Zuck on Apple and lessons from the past 24:22 Future of AI: Llama 3 and beyond 26:43 Prediction: Billions of personalized AI agents 31:32 Factors to changing anti-AI sentiment
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Exclusive: Meta just released Llama 3.1 405B — the first-ever open-sourced frontier AI model, beating top closed models like GPT-4o across several benchmarks. I sat down with Mark Zuckerberg, diving into why this marks a major moment in AI history. Timestamps: 00:00 Intro 00:38 Meta’s Llama 3.1 rundown 03:44 Real-world use cases for Llama 3.1 06:15 Educating developers on open-source AI tools 09:43 Societal implications of open-source AI 13:00 Balancing power and managing bad actors 14:40 Open source and global competition 16:59 Accelerating innovation and economic growth 20:04 Zuck on Apple and lessons from the past 24:22 Future of AI: Llama 3 and beyond 26:43 Prediction: Billions of personalized AI agents 31:32 Factors to changing anti-AI sentiment

Rowan Cheung

2,657,885 просмотров • 2 лет назад

Llama 3.3 70B 4-bit runs nicely on a 64GB M3 Max with in MLX LM (~10 toks/sec). Would be even faster on an M4 Max. Yesterday's server-only 405B is today's laptop 70B:
0:33

Llama 3.3 70B 4-bit runs nicely on a 64GB M3 Max with in MLX LM (~10 toks/sec). Would be even faster on an M4 Max. Yesterday's server-only 405B is today's laptop 70B:

Awni Hannun

110,534 просмотров • 1 год назад

DeepSeek R1 671B is ridiculously good, but running at 158 tokens per second is something out of this world. A model *this good* running *this fast* is 3 years ahead of this time. The secret: DeepSeek in this short video isn't running on GPUs. It's running on custom-made chips! This is running on SambaNova and their SN40L chips, which are designed and optimized for running AI workflows. SambaNova is sponsoring my work. We designed GPUs to run games and later realized we could use them for AI. This is very different from creating a chip specifically for AI from the ground up. Just think about this for a second: One single SNL40 chip can simultaneously hold 100+ models (trillions of parameters) in memory! An agentic workflow that uses multiple models simultaneously won't need to swap models from memory even once! By the way, the Llama family of models *screams* on the SambaNova Cloud. Here are some numbers from my latest tests: • Llama 3.3 70B: 367.32 t/s • Llama 3.2 1B: 2381.82 t/s • Llama 3.2 3B: 1335.71 t/s • Llama 3.1 8B: 929.58 t/s • Llama 3.1 70B: 369.16 t/s • Llama 3.1 405B: 103.37 t/s You can access all of these models for free!
1:34

DeepSeek R1 671B is ridiculously good, but running at 158 tokens per second is something out of this world. A model *this good* running *this fast* is 3 years ahead of this time. The secret: DeepSeek in this short video isn't running on GPUs. It's running on custom-made chips! This is running on SambaNova and their SN40L chips, which are designed and optimized for running AI workflows. SambaNova is sponsoring my work. We designed GPUs to run games and later realized we could use them for AI. This is very different from creating a chip specifically for AI from the ground up. Just think about this for a second: One single SNL40 chip can simultaneously hold 100+ models (trillions of parameters) in memory! An agentic workflow that uses multiple models simultaneously won't need to swap models from memory even once! By the way, the Llama family of models *screams* on the SambaNova Cloud. Here are some numbers from my latest tests: • Llama 3.3 70B: 367.32 t/s • Llama 3.2 1B: 2381.82 t/s • Llama 3.2 3B: 1335.71 t/s • Llama 3.1 8B: 929.58 t/s • Llama 3.1 70B: 369.16 t/s • Llama 3.1 405B: 103.37 t/s You can access all of these models for free!

Santiago

131,099 просмотров • 1 год назад

Exciting day today as Meta launches its new Llama 3.1 models and they’re available in Bedrock immediately. Llama 3.1 is a substantial step forward and the models (highlighted by the powerful 405B model) are impressive and powerful. Customers are gonna love these high performance models. Giddy up!
0:41

Exciting day today as Meta launches its new Llama 3.1 models and they’re available in Bedrock immediately. Llama 3.1 is a substantial step forward and the models (highlighted by the powerful 405B model) are impressive and powerful. Customers are gonna love these high performance models. Giddy up!

Andy Jassy

45,000 просмотров • 2 лет назад

Our Llama-3.1-Nemotron-70B-Instruct model is a leading model on the 🏆 Arena Hard benchmark (85) from Arena. Arena Hard uses a data pipeline to build high-quality benchmarks from live data in Chatbot Arena, and is known for its predictive ability of Chatbot Arena Elo score as well as separability between helpful and less helpful models. Use our customized model Llama-3.1-Nemotron-70B to improve the helpfulness of LLM generated responses in your applications. 📥 Try on our API catalog: 📥 On GitHub: 📥 Or on Hugging Face:
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Our Llama-3.1-Nemotron-70B-Instruct model is a leading model on the 🏆 Arena Hard benchmark (85) from Arena. Arena Hard uses a data pipeline to build high-quality benchmarks from live data in Chatbot Arena, and is known for its predictive ability of Chatbot Arena Elo score as well as separability between helpful and less helpful models. Use our customized model Llama-3.1-Nemotron-70B to improve the helpfulness of LLM generated responses in your applications. 📥 Try on our API catalog: 📥 On GitHub: 📥 Or on Hugging Face:

NVIDIA AI Developer

140,870 просмотров • 1 год назад