Created: by Pradeep Gowda . Updated: Oct 09, 2023 Tagged: llm · deep-learning · chatgpt

large language models

See also generative-ai page. and smol-llm , transformer-math , LlamaIndex , RAG , and local-llm , llm-embedding

Introductory Materials

Generative AI exists because of the transformer – A visual story from Financial Times; Sept 2023.

Large language models, explained with a minimum of math and jargon

Study Guides




An observation on Generalization - YouTube by Ilya Sutskever (OpenAI); Aug 14, 2023.

Prompt Engineering

Open source models

Stuff you can run on your computer

smol-ai/developer: with 100k context windows on the way, it’s now feasible for every dev to have their own smol developer

How is LLaMa.cpp possible? how can we run llama.cpp on local machines when the expectation is that large models need expensive GPUS (eg: A100) to run

Introducing Code Llama, a state-of-the-art large language model for coding Code Llama is a code-specialized version of Llama 2 that was created by further training Llama 2 on its code-specific datasets, sampling more data from that same dataset for longer. Essentially, Code Llama features enhanced coding capabilities, built on top of Llama 2. It can generate code, and natural language about code, from both code and natural language prompts (e.g., “Write me a function that outputs the fibonacci sequence.”) It can also be used for code completion and debugging. It supports many of the most popular languages being used today, including Python, C++, Java, PHP, Typescript (Javascript), C#, and Bash.

Ask HN: Cheapest way to run local LLMs? | Hacker News

LLMs in your language

All languages are NOT created (tokenized) equal

Small Language Models

Using LLMs


LlamaIndex 🦙 0.8.13

Haystack | Haystack Open-source LLM framework to build production-ready applications . > Use the latest LLMs: hosted models by OpenAI or Cohere, open-source LLMs, or other pre-trained models > All tooling in one place: preprocessing, pipelines, agents & tools, prompts, evaluation and finetuning > Choose your favorite database: Elasticsearch, OpenSearch, Weaviate, Pinecone, Qdrant, Milvus and more > Scale to millions of documents: use Haystack’s proven retrieval architecture > Compare it to LangChainAI

GPT4All A free-to-use, locally running, privacy-aware chatbot. No GPU or internet required.

AI Proxy

an AI proxy that lets you use a variety of providers (OpenAI, Anthropic, LLaMa2, Mistral, and others) behind a single interface w/ caching & API key management.

MLC LLM Machine Learning Compilation for Large Language Models (MLC LLM) is a high-performance universal deployment solution that allows native deployment of any large language models with native APIs with compiler acceleration. The mission of this project is to enable everyone to develop, optimize and deploy AI models natively on everyone’s devices with ML compilation techniques.

Project Overview Project Overview of MLC LLM

[[Multimodal Learning]]



OWASP | Top 10 for Large Language Models

Operational Issues

Benchmarking lLMs

LLM Benchmark Report for: NousResearch/Redmond-Puffin-13B