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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...

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AI at Meta

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1,268,238 Aufrufe • vor 1 Jahr •via X (Twitter)

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AI at Metavor 1 Jahr

Training a model as large and capable as Llama 3.1 405B was no simple task. The model was trained on over 15 trillion tokens over the course of several months requiring over 16K @NVIDIA H100 GPUs — making it the first Llama model ever trained at this scale. We also used the 405B parameter model to improve the post-training quality of our smaller models.

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AI at Metavor 1 Jahr

With Llama 3.1, we evaluated performance on >150 benchmark datasets spanning a wide range of languages — in addition to extensive human evaluations in real-world scenarios. These results show that the 405B competes with leading closed source models like GPT-4, Claude 2 and Gemini Ultra across a range of tasks. Our upgraded Llama 3.1 8B & 70B models are also best-in-class, outperforming other models at their size while also delivering a better balance of helpfulness and safety than their predecessors. These smaller models support the same improved 128K token context window, multilinguality, improved reasoning and state-of-the-art tool use to enable more advanced use cases.

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AI at Metavor 1 Jahr

We’ve also updated our license to allow developers to use the outputs from Llama models — including 405B — to improve other models for the first time. We’re excited about how this will enable new advancements in the field through synthetic data generation and model distillation workflows, capabilities that have never been achieved at this scale in open source.

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AI at Metavor 1 Jahr

As Mark Zuckerberg shared in an open letter this morning: we believe that open source will ensure that more people around the world have access to the benefits and opportunities of AI, that power isn't concentrated in the hands of a small few, and that the technology can be deployed more evenly and safely across society. That’s why we continue to take steps on the path for open source AI to become the industry standard. Read the letter ⬇️

Profilbild von Vaibhav (VB) Srivastav
Vaibhav (VB) Srivastavvor 1 Jahr

Congratulations on the release @AIatMeta! Thanks for your unwavering support for Open Source 🤗 I put down some notes from the release below!

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AI at Metavor 1 Jahr

Open source AI is the path forward. ❤️

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Luis Cezevor 1 Jahr

Fantastic to partner with Meta on this! Thank you Meta! And big thank you to the incredible team at OctoAI putting the models on the platform at launch! 🚀🙏🐙

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Prime Intellectvor 1 Jahr

Awesome research and progress towards open source AGI!!

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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!
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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 Aufrufe • vor 1 Jahr

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FlowiseAI

48,208 Aufrufe • vor 1 Jahr

You can now try Llama 3.1 405B for free (link below)! ​ This is the largest open-source model out there, and for the first time, an open model is competitive with closed models. ​ This time around, Meta did something new: Llama 3.1 has a license that allows developers to use it to enhance other models. For the first time, you can distill Llama 3.1 405B's capabilities into a smaller, more practical model for your use case. ​ First, here is the link where you can play with Llama 3.1 for free: ​ The model is hosted in Tune Studio, an end-to-end platform for developing applications using Large Language Models. They are sponsoring this post. ​ Take a look at the attached video. It will show you how you can fine-tune a simple model using Llama 3.1 without leaving the platform: ​ 1. You can create an empty dataset 2. Use the playground to generate and record interactions with Llama 3.1 3. Modify the dataset directly using the playground 4. Export the data and fine-tune a smaller model ​ Fast and easy! ​ As long as you have a web browser, you can start experimenting with fine-tuning and Llama 3.1. That's all it takes!
0:46

You can now try Llama 3.1 405B for free (link below)! ​ This is the largest open-source model out there, and for the first time, an open model is competitive with closed models. ​ This time around, Meta did something new: Llama 3.1 has a license that allows developers to use it to enhance other models. For the first time, you can distill Llama 3.1 405B's capabilities into a smaller, more practical model for your use case. ​ First, here is the link where you can play with Llama 3.1 for free: ​ The model is hosted in Tune Studio, an end-to-end platform for developing applications using Large Language Models. They are sponsoring this post. ​ Take a look at the attached video. It will show you how you can fine-tune a simple model using Llama 3.1 without leaving the platform: ​ 1. You can create an empty dataset 2. Use the playground to generate and record interactions with Llama 3.1 3. Modify the dataset directly using the playground 4. Export the data and fine-tune a smaller model ​ Fast and easy! ​ As long as you have a web browser, you can start experimenting with fine-tuning and Llama 3.1. That's all it takes!

Santiago

55,609 Aufrufe • vor 1 Jahr

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

97,505 Aufrufe • vor 1 Jahr

"Introducing Multimodal Llama 3.2": As promised two weeks ago, here's the short course on Meta's latest open model! This short course is created with Meta and taught by Amit Sangani, Director of AI Partner Engineering at Meta. Meta’s Llama family of models is leading the way in open models, allowing anyone to download, customize, fine-tune, or build new applications on top of them. Learn about the vision capabilities of the Llama 3.2, and use it for image classification, prompting, tokenization, tool-calling. You'll also learn about the open-source Llama stack, which gives building blocks for many different stages of the LLM application life cycle. In detail, you’ll: - Learn what are the features of Meta's four newest models, and when to use which Llama model. - Learn best practices for multimodal prompting, with applications to advanced image reasoning, illustrated by many examples: Understanding errors on a car dashboard, adding up the total of photographed restaurant receipts, grading written math homework. - Use different roles—system, user, assistant, ipython—in the Llama 3.1 and 3.2 models and the prompt format that identifies those roles. - Understand how Llama uses the tiktoken tokenizer, and how it has expanded to a 128k vocabulary size that improves encoding efficiency and multilingual support. - Learn how to prompt Llama to call built-in and custom tools (functions) with examples for web search and solving math equations. - Learn about Llama Stack, a standardized interface for common toolchain components like fine-tuning or synthetic data generation, useful for building agentic applications. By the end of this course, you’ll be equipped to build out new applications with the new Llama 3.2. Thank you to Ahmad Al-Dahle, Amit Sangani, and the whole AI at Meta team AI at Meta for all the hard work on Llama 3.2 — we’re excited to make these open models even more accessible to more developers with this new course! Please sign up here!
2:53

"Introducing Multimodal Llama 3.2": As promised two weeks ago, here's the short course on Meta's latest open model! This short course is created with Meta and taught by Amit Sangani, Director of AI Partner Engineering at Meta. Meta’s Llama family of models is leading the way in open models, allowing anyone to download, customize, fine-tune, or build new applications on top of them. Learn about the vision capabilities of the Llama 3.2, and use it for image classification, prompting, tokenization, tool-calling. You'll also learn about the open-source Llama stack, which gives building blocks for many different stages of the LLM application life cycle. In detail, you’ll: - Learn what are the features of Meta's four newest models, and when to use which Llama model. - Learn best practices for multimodal prompting, with applications to advanced image reasoning, illustrated by many examples: Understanding errors on a car dashboard, adding up the total of photographed restaurant receipts, grading written math homework. - Use different roles—system, user, assistant, ipython—in the Llama 3.1 and 3.2 models and the prompt format that identifies those roles. - Understand how Llama uses the tiktoken tokenizer, and how it has expanded to a 128k vocabulary size that improves encoding efficiency and multilingual support. - Learn how to prompt Llama to call built-in and custom tools (functions) with examples for web search and solving math equations. - Learn about Llama Stack, a standardized interface for common toolchain components like fine-tuning or synthetic data generation, useful for building agentic applications. By the end of this course, you’ll be equipped to build out new applications with the new Llama 3.2. Thank you to Ahmad Al-Dahle, Amit Sangani, and the whole AI at Meta team AI at Meta for all the hard work on Llama 3.2 — we’re excited to make these open models even more accessible to more developers with this new course! Please sign up here!

Andrew Ng

131,606 Aufrufe • vor 1 Jahr

New short course: Prompt Engineering with Llama 2, built in collaboration with Meta AI at Meta, and taught by Amit Sangani! Meta's Llama 2 has been game-changing for AI. Building with open source lets you control your own data, scrutinize errors, update (or not) the models as you please, and work alongside the global community advancing open models. Llama isn't a single model, it's a collection of models. In this course, you'll: - Learn the differences between different Llama 2 flavors, and when to use each. - Prompt the Llama chat models -- you'll also see how Llama's instruction tags work -- so they can help you with day-to-day tasks, like writing or summarization. - Use advanced prompting, like few-shot prompting for classification, and chain-of-thought prompting for solving logic problems. - Use specialized models in the Llama collection for specific tasks, like Code Llama to help you write, analyze, and improve code, and Llama Guard, which checks prompts and model responses for harmful content. The course also touches on how to run Llama 2 locally on your own computer. I hope you’ll take this course and try out these powerful, open models!
4:14

New short course: Prompt Engineering with Llama 2, built in collaboration with Meta AI at Meta, and taught by Amit Sangani! Meta's Llama 2 has been game-changing for AI. Building with open source lets you control your own data, scrutinize errors, update (or not) the models as you please, and work alongside the global community advancing open models. Llama isn't a single model, it's a collection of models. In this course, you'll: - Learn the differences between different Llama 2 flavors, and when to use each. - Prompt the Llama chat models -- you'll also see how Llama's instruction tags work -- so they can help you with day-to-day tasks, like writing or summarization. - Use advanced prompting, like few-shot prompting for classification, and chain-of-thought prompting for solving logic problems. - Use specialized models in the Llama collection for specific tasks, like Code Llama to help you write, analyze, and improve code, and Llama Guard, which checks prompts and model responses for harmful content. The course also touches on how to run Llama 2 locally on your own computer. I hope you’ll take this course and try out these powerful, open models!

Andrew Ng

162,798 Aufrufe • vor 2 Jahren

Llama 3.2 features 11B & 90B models, our first multimodal Llama models with support for vision tasks. These models can take in both image and text prompts to deeply understand and reason on inputs.
0:38

Llama 3.2 features 11B & 90B models, our first multimodal Llama models with support for vision tasks. These models can take in both image and text prompts to deeply understand and reason on inputs.

AI at Meta

121,502 Aufrufe • vor 1 Jahr

With Llama 3.2 we released our first-ever lightweight Llama models: 1B & 3B. These models empower developers to build personalized, on-device agentic applications with capabilities like summarization, tool use and RAG where data never leaves the device.
0:45

With Llama 3.2 we released our first-ever lightweight Llama models: 1B & 3B. These models empower developers to build personalized, on-device agentic applications with capabilities like summarization, tool use and RAG where data never leaves the device.

AI at Meta

153,348 Aufrufe • vor 1 Jahr

Exciting update for AI developers! The Hugging Face Hub is now more natively integrated into Google Cloud Vertex AI Model Garden. Search through thousands of open Generative AI models from Hugging Face models & deploy them with one click to Vertex AI or GKE. 🤯 What's new: 🔎 Browse and search thousands of Hugging Face models directly within the Vertex AI Model Garden and filter based on what is currently trending in the community. 🚀 Accelerate your AI projects by leveraging readily available one-click deploy your model to Vertex AI or Google Kubernetes Engine (GKE). ⭐️ Featuring popular open models from Black Forest Labs FLUX.1, AI at Meta Llama 3.1, Mistral AI, Google DeepMind Gemma, and countless others. Get Started:
0:38

Exciting update for AI developers! The Hugging Face Hub is now more natively integrated into Google Cloud Vertex AI Model Garden. Search through thousands of open Generative AI models from Hugging Face models & deploy them with one click to Vertex AI or GKE. 🤯 What's new: 🔎 Browse and search thousands of Hugging Face models directly within the Vertex AI Model Garden and filter based on what is currently trending in the community. 🚀 Accelerate your AI projects by leveraging readily available one-click deploy your model to Vertex AI or Google Kubernetes Engine (GKE). ⭐️ Featuring popular open models from Black Forest Labs FLUX.1, AI at Meta Llama 3.1, Mistral AI, Google DeepMind Gemma, and countless others. Get Started:

Philipp Schmid

34,747 Aufrufe • vor 1 Jahr

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

130,919 Aufrufe • vor 1 Jahr

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:
0:24

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

273,127 Aufrufe • vor 1 Jahr

Introducing Veo 3.1 and Veo 3.1 Fast, our latest state of the art video models with: - richer native audio - better cinematic styles - reference to video - transitions between frames - video extensions
1:12

Introducing Veo 3.1 and Veo 3.1 Fast, our latest state of the art video models with: - richer native audio - better cinematic styles - reference to video - transitions between frames - video extensions

Logan Kilpatrick

255,200 Aufrufe • vor 7 Monaten

Base models are insanely powerful, and far more creative than instruction-tuned models like GPT-4 and Claude. But few people have actually had a chance to use them. That changes today. I've built a playground that allows you to interact with Llama 3.1 405B Base:
0:24

Base models are insanely powerful, and far more creative than instruction-tuned models like GPT-4 and Claude. But few people have actually had a chance to use them. That changes today. I've built a playground that allows you to interact with Llama 3.1 405B Base:

Matt Shumer

117,782 Aufrufe • vor 1 Jahr

🚨 Big news for AI innovation: Claude Opus 4 and Claude Sonnet 4, Anthropic's most advanced models, are now available in Amazon Bedrock. These powerful models offer hybrid reasoning, 200K token context windows, and are designed for AI agents. From financial analysis to high-quality writing, to enhanced reasoning, coding, agentic capabilities and more—all with the enterprise-grade security of Amazon Web Services.
0:30

🚨 Big news for AI innovation: Claude Opus 4 and Claude Sonnet 4, Anthropic's most advanced models, are now available in Amazon Bedrock. These powerful models offer hybrid reasoning, 200K token context windows, and are designed for AI agents. From financial analysis to high-quality writing, to enhanced reasoning, coding, agentic capabilities and more—all with the enterprise-grade security of Amazon Web Services.

Amazon

123,022 Aufrufe • vor 1 Jahr

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:
0:43

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

140,699 Aufrufe • vor 1 Jahr

We believe an open approach is the right one for the development of today's Al models. Today, we’re releasing Llama 2, the next generation of Meta’s open source Large Language Model, available for free for research & commercial use. Details ➡️
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We believe an open approach is the right one for the development of today's Al models. Today, we’re releasing Llama 2, the next generation of Meta’s open source Large Language Model, available for free for research & commercial use. Details ➡️

AI at Meta

1,234,337 Aufrufe • vor 2 Jahren

As we wrap up 2024, we're sharing an update on our progress with Llama and the impact it’s having around the world. Read the full update here ➡️ A few highlights from 2024 📈 Llama has been downloaded over 650M times, doubling in just three months. 🌏 License approvals for Llama have more than doubled globally, with significant growth in emerging markets. 🤗 There are now over 85,000 Llama derivative models on Hugging Face alone — a 5x increase from the start of the year. ❤️ We’re continuing to see Llama being used across the industry with new examples and innovation from Block, Accenture and LinkedIn — among others. Open source AI is shaping the future. As we look to 2025, the pace of innovation will only increase as we work to make Llama the industry standard for building on AI.
1:04

As we wrap up 2024, we're sharing an update on our progress with Llama and the impact it’s having around the world. Read the full update here ➡️ A few highlights from 2024 📈 Llama has been downloaded over 650M times, doubling in just three months. 🌏 License approvals for Llama have more than doubled globally, with significant growth in emerging markets. 🤗 There are now over 85,000 Llama derivative models on Hugging Face alone — a 5x increase from the start of the year. ❤️ We’re continuing to see Llama being used across the industry with new examples and innovation from Block, Accenture and LinkedIn — among others. Open source AI is shaping the future. As we look to 2025, the pace of innovation will only increase as we work to make Llama the industry standard for building on AI.

AI at Meta

109,224 Aufrufe • vor 1 Jahr

Open models are accelerating development and deployment across agentic AI, physical AI, and a growing range of industries. ✨ “We have billions of dollars of supercomputers in operation, so we can develop our open models,” said NVIDIA CEO Jensen Huang in a recent keynote. “That work is starting to attract attention across industries worldwide, as we build frontier AI models in many different domains.” This includes leading open models from NVIDIA, including: ⚙️ NVIDIA Nemotron for agentic AI ⚙️ NVIDIA Cosmos and GR00T for physical AI ⚙️ NVIDIA Alpamayo for autonomous vehicles ⚙️ NVIDIA Clara for biomedical AI Learn more about open source and AI ➡️
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Open models are accelerating development and deployment across agentic AI, physical AI, and a growing range of industries. ✨ “We have billions of dollars of supercomputers in operation, so we can develop our open models,” said NVIDIA CEO Jensen Huang in a recent keynote. “That work is starting to attract attention across industries worldwide, as we build frontier AI models in many different domains.” This includes leading open models from NVIDIA, including: ⚙️ NVIDIA Nemotron for agentic AI ⚙️ NVIDIA Cosmos and GR00T for physical AI ⚙️ NVIDIA Alpamayo for autonomous vehicles ⚙️ NVIDIA Clara for biomedical AI Learn more about open source and AI ➡️

NVIDIA AI

19,296 Aufrufe • vor 4 Monaten