Nicolay Gerold

Text embeddings are a critical piece of many pipelines, from search, to RAG, to vector databases and more. Most embedding models are BERT/Transformer-based and typically have short context lengths (e.g., 512). That’s only about two pages of text, but documents can be very long – books, legal cases, TV screenplays, code repositories, etc can be tens... See more

A new v0.4.0 release of lm-evaluation-harness is available !

New updates and features include:

• Internal refactoring


• Config-based task creation and configuration


• Easier import and sharing of externally-defined task config YAMLs


• Support for Jinja2 prompt design, easy modification of prompts + prompt imports from Promptsource


• More advanced configuration

... See more

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# Definition of used LLM

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def graphPrompt(input: str, metadata={}, model="mixtral:latest"):

if model == None:

model = "mixtral:latest"

chunk_id = metadata.get('chunk_id', None)

# model_info =... See more

Beta alanine delays the build up of acid → before exercise.

• Django: It's like a superpower for solo developers. The longer you work in the industry, the more you appreciate the conventions it uses. A monolithic framework can get you really, really far. To me, it's about predictable software that's fast in every way that matters. By the way, I talk more about this topic on my other blog post Choose Boring

... See more

The motor, auditory, and visual systems teach themselves. Try out different parameters and find the ones which make the behavior better and then focus on these. Isolate the errors and make a variety of errors in a particular aspect of the motor movement to signal it is plastic.

The book Clean Code introduces three laws of TDD [1]:

1. Write a failing unit test first before you start writing production code.


2. Write not more of a unit test than is sufficient to fail.


3. Write not more production code than is sufficient to pass the currently failing test.

So, the tests are written before the production code. This leads to the developer... See more

“I look for features from data scientists, [who have ideas of] things that are correlated with what I’m trying to predict.” We found that organizations explicitly prioritized cross-team collaboration as part of their ML culture. Md3 said: We really think it’s important to bridge that gap between what’s often, you know, a [subject matter expert] in... See more

You can think your way into solving a deterministic system, but you cannot think your way into solving a probabilistic system.

The first thing that I want to call out is that deterministic software has edge cases, while probabilistic software has long tails.

I find that a lot of junior folks try to really think hard about edge cases around... See more