LLMs

⚡ LitGPT

Pretrain, finetune, evaluate, and deploy 20+ LLMs on your own data

Uses the latest state-of-the-art techniques:

✅ flash attention ✅ fp4/8/16/32 ✅ LoRA, QLoRA, Adapter (v1, v2) ✅ FSDP ✅ 1-1000+ GPUs/TPUs

Lightning AI • Models • Quick start • Inference • Finetune • Pretrain • Deploy • Features • Training recipes (YAML)

Finetune, pretrain and... See more

The OpenAI Assistants API offers more than a simple prompt-sharing interface; it provides a sophisticated framework for AI interactions. It allows for persistent conversation sessions with automatic context management (Threads), structured interactions (Messages and Runs), integration with various tools for enhanced capabilities, customization... See more

In the simplest form, we can use the model’s detection confidence to determine a score. But even here there are quite a few options to choose from:

• Lowest confidence - the score is the lowest confidence of all detected objects


• Average confidence - average of all confidences of detected objects


• Minimizing confidence delta - difference between

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• Right now, GPTs are the easiest way of sharing structured prompts, which are programs, written in plain English (or another language), that can get the AI to do useful things. I discussed creating structured prompts last week, and all the same techniques apply, but the GPT system makes structured prompts more powerful and much easier to create,

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Menlo Ventures released a report on ‘The State of Generative AI in the Enterprise’ and found that adoption is trailing the hype. Details below:

Generative AI still represents less than 1% of cloud spend by surveyed enterprises, including just an 8% increase in 2023.

Safety and ROI continue to be prime concerns, and the tangible advantages of being... See more

What’s the best way for an end user to organize and explore millions of latent space features?

I’ve found tens of thousands of interpretable features in my experiments, and frontier labs have demonstrated results with a thousand times more features in production-scale models. No doubt, as interpretability techniques advance, we’ll see feature maps... See more

Generative AI can automate simple tasks

By automating simpler, tedious tasks (generating boilerplate code, fixing linter errors, generating unit tests, etc.), generative AI can help engineers focus on more complex tasks.

Generative AI can improve quality & reliability

Since generative AI models are trained on large codebases, they have the potential... See more

The quality of dataset is 95% of everything. The rest 5% is not to ruin it with bad parameters.