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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!show more

Andrew Ng

1,535,057 subscribers

162,798 Aufrufe • vor 2 Jahren •via X (Twitter)

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10 Kommentare

Profilbild von Sambhav Gupta

Sambhav Guptavor 2 Jahren

@AIatMeta @asangani7 Looks Interesting. Signed up 🤘

Profilbild von Reverie

Reverievor 2 Jahren

@AIatMeta @asangani7 Sounds great! I watched the ChatGPT Prompt Engineering for Developer short course and learned a lot. This could be another incredible one! Appreciate it.

Profilbild von Felipe Chaves

Felipe Chavesvor 2 Jahren

@AIatMeta @asangani7 That sounds interesting. It's always good to see new courses in AI.

Profilbild von Roxane

Roxanevor 2 Jahren

@AIatMeta @asangani7

Profilbild von Christian Baumberger

Christian Baumbergervor 2 Jahren

@AIatMeta @asangani7 Step 1: Pet the Llama. Step 2: Watch the magic happen. 🦙🔮

Profilbild von observations and suggestions

observations and suggestionsvor 2 Jahren

@AIatMeta @asangani7 Cool!

Profilbild von JiaLong Wang

JiaLong Wangvor 2 Jahren

@AIatMeta @asangani7 Great! i hope it can help me to use ai tools more efficiently

Profilbild von Omar Al-Jadda 🎾

Omar Al-Jadda 🎾vor 2 Jahren

@AIatMeta @asangani7 This is looks really awesome, I thoroughly enjoy toying with offline AI models, can't wait to take the course!

Profilbild von Wen xudong ♥Deep learning engineer

Wen xudong ♥Deep learning engineervor 2 Jahren

@AIatMeta @asangani7 Interesting

Profilbild von Anshul Panwar

Anshul Panwarvor 2 Jahren

@AIatMeta @asangani7 Super good and helpful

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224,534 Aufrufe • vor 2 Jahren

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Santiago

97,505 Aufrufe • vor 1 Jahr

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Santiago

130,934 Aufrufe • vor 1 Jahr

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30,236 Aufrufe • vor 1 Jahr

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Wes Roth

10,233 Aufrufe • vor 2 Jahren

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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

DeepSeek-R1. Now running *locally* on your Umbrel. Yes, you can now self-host open source AI models like R1, Llama, and more on your home cloud — thanks to ollama and Open WebUI. Download Open WebUI and Ollama from the Umbrel App Store to get started.

DeepSeek-R1. Now running locally on your Umbrel. Yes, you can now self-host open source AI models like R1, Llama, and more on your home cloud — thanks to ollama and Open WebUI. Download Open WebUI and Ollama from the Umbrel App Store to get started.

Umbrel ☂️

36,562 Aufrufe • vor 1 Jahr

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You can now fine-tune Llama 3 without writing a single line of code! We are moving at breakneck speed. I recorded a video to show you how to fine-tune any open-source model in a few minutes. I'm using a GPT capable of taking a problem and turning it into a fine-tuned model that will solve it. You don't have to write any code. You only need to explain to a GPT what problem you want to solve and tell it you want to use Llama 3. For example, "fine-tune Llama 3" or "deploy zephyr." It feels magic. The system will recommend a dataset and fine-tune the model for you. I'm using Monster API, a platform that specializes in making fine-tuning and deploying open-source models easy and fast. Their stack is well-optimized to maximize fine-tuning efficiency using techniques like Q-Lora and vLLM. They are behind the GPT. Here is what you need to do: 1. Create an account at 2. Load the GPT with the link below This is as simple as it gets. When you are done, you can click a button to deploy the model and start using it. I have 10,000 free credits for anyone using the code "SANTIAGO" in the dashboard. You can use these credits to access, fine-tune, and deploy these open-source models. You can also keep up with their latest updates, and get free credits and special offers on their Discord server:

Santiago

324,586 Aufrufe • vor 2 Jahren

Today, we’re releasing our research preview ( to let you look inside your AI. We've created a desktop interface that helps you understand and control Llama 3's behavior. You can 1) see Llama 3's internal features (the internal building blocks of its responses) and 2) precisely adjust these features to create new Llama variants. Try it out and share your findings with #GoodfireAI

Today, we’re releasing our research preview ( to let you look inside your AI. We've created a desktop interface that helps you understand and control Llama 3's behavior. You can 1) see Llama 3's internal features (the internal building blocks of its responses) and 2) precisely adjust these features to create new Llama variants. Try it out and share your findings with #GoodfireAI

Goodfire

67,131 Aufrufe • vor 1 Jahr