Simon Willison’s Weblog

llm-gpt4all. New release of my LLM plugin which builds on Nomic's excellent gpt4all Python library. I've upgraded to their latest version which adds support for Llama 3 8B Instruct, so after a 4.4GB model download this works:

llm -m Meta-Llama-3-8B-Instruct "say hi in Spanish"

# 20th April 2024, 5:58 pm / plugins, projects, ai, generative-ai, llama, homebrew-llms, llms, llm, nomic

llm-nomic-api-embed. My new plugin for LLM which adds API access to the Nomic series of embedding models. Nomic models can be run locally too, which makes them a great long-term commitment as there’s no risk of the models being retired in a way that damages the value of your previously calculated embedding vectors.

# 31st March 2024, 3:17 pm / plugins, projects, ai, embeddings, llm, nomic

Adaptive Retrieval with Matryoshka Embeddings (via) Nomic Embed v1 only came out two weeks ago, but the same team just released Nomic Embed v1.5 trained using a new technique called Matryoshka Representation.

This means that unlike v1 the v1.5 embeddings are resizable—instead of a fixed 768 dimension embedding vector you can trade size for quality and drop that size all the way down to 64, while still maintaining strong semantically relevant results.

Joshua Lochner build this interactive demo on top of Transformers.js which illustrates quite how well this works: it lets you embed a query, embed a series of potentially matching text sentences and then adjust the number of dimensions and see what impact it has on the results.

# 15th February 2024, 4:19 am / ai, llms, embeddings, nomic, transformers-js

llm-sentence-transformers 0.2. I added a new --trust-remote-code option when registering an embedding model, which means LLM can now run embeddings through the new Nomic AI nomic-embed-text-v1 model.

# 4th February 2024, 7:39 pm / plugins, projects, transformers, ai, embeddings, llm, nomic

Introducing Nomic Embed: A Truly Open Embedding Model. A new text embedding model from Nomic AI which supports 8192 length sequences, claims better scores than many other models (including OpenAI’s new text-embedding-3-small) and is available as both a hosted API and a run-yourself model. The model is Apache 2 licensed and Nomic have released the full set of training data and code.

From the accompanying paper: “Full training of nomic-embed-text-v1 can be conducted in a single week on one 8xH100 node.”

# 3rd February 2024, 11:13 pm / ai, embeddings, nomic