Simon Willison’s Weblog: llm-cerebras

Source URL: https://simonwillison.net/2024/Oct/25/llm-cerebras/
Source: Simon Willison’s Weblog
Title: llm-cerebras

Feedly Summary: llm-cerebras
Cerebras (previously) provides Llama LLMs hosted on custom hardware at ferociously high speeds.
GitHub user irthomasthomas built an LLM plugin that works against their API – which is currently free, albeit with a rate limit of 30 requests per minute for their two models.
llm install llm-cerebras
llm keys set cerebras
# paste key here
llm -m cerebras-llama3.1-70b ‘an epic tail of a walrus pirate’

Here’s a video showing the speed of that prompt:

The other model is cerebras-llama3.1-8b.
Tags: llm, llms, ai, generative-ai

AI Summary and Description: Yes

Summary: The text discusses Cerebras’ offering of Llama LLMs hosted on customized hardware, which provides high-speed performance. It also highlights an LLM plugin developed by a GitHub user, demonstrating an example command.

Detailed Description:
The content relates to advanced technology in the AI and LLM (Large Language Model) space, which is pertinent for professionals in AI security, infrastructure, and software development. Key insights and implications include:

– **Cerebras Technology**:
– Cerebras specializes in Llama LLMs, emphasizing their hosting on custom hardware.
– The high speeds provided by this infrastructure could be significant for applications requiring rapid data processing and model inference.

– **LLM Plugin Development**:
– The text mentions a GitHub user who created an LLM plugin that interacts with Cerebras’ API.
– This plugin is currently available for free, with a limitation on request rates (30 requests per minute), indicating accessibility for developers.

– **Examples of Use**:
– A sample command is provided to demonstrate how users can interact with Cerebras’ LLMs, showcasing practical application scenarios.

– **Models Available**:
– Two models are highlighted: cerebras-llama3.1-70b and cerebras-llama3.1-8b, pointing to a range of applications depending on the computational requirements.

– **Implications for Security and Compliance**:
– The discussion about hosting models on custom hardware raises questions about security management, data handling, and compliance with regulations related to AI and cloud security.
– As LLMs become more integrated into various solutions, the need for robust security measures will be critical, particularly surrounding API access and rate limits.

This content is relevant for stakeholders in AI deployment, emphasizing the intersection of hardware infrastructure and software development while raising awareness of security considerations in AI tool usage.