morgan (Morgan McGuire)

posted an update about 1 month ago

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1290

Llama 3.1 405B Instruct beats GPT-4o on MixEval-Hard

Just ran MixEval for 405B, Sonnet-3.5 and 4o, with 405B landing right between the other two at 66.19

The GPT-4o result of 64.7 replicated locally but Sonnet-3.5 actually scored 70.25/69.45 in my replications 🤔 Still well ahead of the other 2 though.

Sammple of 1 of the eval calls here: https://wandb.ai/morgan/MixEval/weave/calls/07b05ae2-2ef5-4525-98a6-c59963b76fe1

Quick auto-logging tracing for openai-compatible clients and many more here: https://wandb.github.io/weave/quickstart/

posted an update 7 months ago

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Fine-tuning LLMs is rad, but how do you manage all your checkpoints and evals in a production setting?

We partnered with @hamel to ship an Enterprise Model Management course packed full of learnings for those training, evaluating and deploying models at work.

Topics include:
- What webhooks are & how to use them to create integrations with different tools
- How to automate train -> eval runs
- Improving model governance and documentation
- Comparing candidate and baseline models
- Design patterns & recipes
- Lots more...

Would love to hear what you think!

👉 https://www.wandb.courses/courses/enterprise-model-management

posted an update 7 months ago

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Delighted to share a course I've learned a ton from about getting better outputs from LLMs

https://www.wandb.courses/courses/steering-language-models

We released it last Thursday (free) and at just 30 minutes of content total, its very information-dense with non-stop learnings covering important concepts around LLM validation, making your approach to LLM prompting more pythonic and quickly covers a basic RAG application at the end.

Would love to hear what ye think!

Morgan McGuire

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