Command R+: A Scalable LLM Built for Business
txt.cohere.com
txt.cohere.com
So now you can do this:
pipx install llm
llm install llm-command-r
llm keys set cohere
<paste Cohere API key here>
llm -m command-r-plus "3 reasons to adopt a sea lion"
One of the most interesting features of the Cohere API models is that they can run web searches and use the results as part of answering the prompt.The plugin adds that as a separate command, which works like this:
llm command-r-search 'What is the LLM CLI tool by simonw?'
Example output (truncated here): The LLM CLI tool is a command-line
utility that allows users to access large
language models. It was created by Simon
Willison and can be installed via pip,
Homebrew or pipx. The tool supports
interactions with remote APIs and models
that can be locally installed and run.
Users can run prompts from the command
line and even build an image search
engine using the CLI tool.
Sources:
- GitHub - simonw/llm: Access large
language models from the command-line -
https://github.com/simonw/llm
- llm, ttok and strip-tags—CLI tools for
working with ChatGPT and other LLMs -
https://simonwillison.net/2023/May/18/cli-tools-for-llms/Maybe not as powerful, but more suitable for running locally on mid range devices.
Cohere API Pricing $ / M input tokens $ / M output tokens
Command R $0.50 $1.50
Command R+ $3.00 $15.00
Command-R: RAG at production scale https://news.ycombinator.com/item?id=39671872
Command R Plus is 104 billion: https://huggingface.co/CohereForAI/c4ai-command-r-plus
Yet the license says:
> License: CC-BY-NC
Besides this snark, seems really good from the benchmark and I'm really glad and grateful people are releasing weights :)
They open weight it so that any enterprise can download it and try it out in their various use cases first.
It's a good strategy.
>2.3 Use Restrictions > You will not use DBRX or DBRX Derivatives or any Output to improve any other large language model (excluding DBRX or DBRX Derivatives).
> Cohere For AI Acceptable Use Policy > generating synthetic data outputs for commercial purposes, including to train, improve, benchmark, enhance or otherwise develop model derivatives, or any products or services in connection with the foregoing.