About this episode
In this episode of Syntax, Wes and Scott talk about understanding the integration of different components in AI models, the choice between traditional models and Language Learning Models (LLM), the relevance of the Hugging Face library, demystify Llama, discuss spaces in AI, and highlight available services. Show Notes 00:25:20 Welcome 00:55:00 Syntax Brought to you by Sentry 01:17:00 Understanding how the pieces fit together 02:31:18 Models or LLM? 04:43:22 What about Hugging Face? 08:05:18 What’s Llama? 08:51:15 What are spaces? 09:29:06 Services available to you 12:26:16 What are tokens in AI? 17:38:18 What is temperature with AI? 20:33:08 Using top_p 21:06:00 Using fine-tuning to extend existing models 22:11:19 Prompts are what you send to the model 23:17:00 Streaming 24:48:17 Embeddings 27:34:17 OpenAI maintains Evals 28:40:14 Different libraries for working with AI Hugging Face Creator of Swift, Tesla Autopilot & Tensorflow. New AI language Mojo with Chris Lattner LLaMA Spaces - Hugging Face OpenAI Anthropic \ Introducing Claude Replicate Fireworks Console gpt-tokenizer playground openai/tiktoken: tiktoken is a fast BPE tokeniser for use with OpenAI’s models. Supper Club × OpenAI, Future of programming, LLMs, and Math with Andrey Mishchenko Raycast Pro Amazon SageMaker (AMS SSPS) openai/evals LangChain PyTorch TensorFlow ai - npm Hit us up on Socials! Syntax: X Instagram Tiktok LinkedIn Threads Wes: X Instagram Tiktok LinkedIn Threads Scott: X Instagram Tiktok LinkedIn Threads