Nicolay Gerold

In general, I see LLMs to be used in two broad categories: data processing, which is more of a worker use-cases, where the latency isn't the biggest issue but rather quality, and in user-interactions, where latency is a big factor. I think for the faster case a faster fallback is necessary. Or you escalate upwards, you first rely on a smaller more... See more

AI Template & SPR Library

Featuring advanced prompts and SPRs

🟢 Website

🔵 LinkedIn

🔴 Patreon

⚪ Discord

Prompt Engineering

Advanced GPTs

Template Library

Marker

Marker converts PDF, EPUB, and MOBI to markdown. It's 10x faster than nougat, more accurate on most documents, and has low hallucination risk.

• Support for a range of PDF documents (optimized for books and scientific papers)


• Removes headers/footers/other artifacts


• Converts most equations to latex


• Formats code blocks and tables


• Support for multiple

... See more

Instant hosting

for Python apps

Hosting for any Python project, big or small. Run AI / ML inference, FastAPI apps, or cron jobs. Beam is the easiest way to run Python on the cloud.

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

Guideline following Large Language Model for Information Extraction

Model Card for GoLLIE 34B

We present GoLLIE, a Large Language Model trained to follow annotation guidelines. GoLLIE outperforms previous approaches on zero-shot Information Extraction and allows the user to perform inferences with annotation schemas defined on the fly. Different from... See more

New prompts dropped @ingo This is very important to my career. You’d better be sure. Are you sure that’s your final answer? Believe in your abilities and strive for excellence. Your hard work will yield remarkable results. Are you sure that's your final answer? It might be worth taking another look.

ETL

The part of the system I'm most proud of, and on which I spent the most effort, is the ETL process.

We had a series of shell scripts for each data source we ingested (there were many), which would pull the data and put it in an s3 bucket.

Then, early in the morning, a cron job would spin up an EC2 instance, which would pull in the latest ETL code... See more