Nicolay Gerold
@nicolaygerold
Nicolay Gerold
Mistral-finetune
mistral-finetune is a light-weight codebase that enables memory-efficient and performant finetuning of Mistral's models. It is based on LoRA, a training paradigm where most weights are frozen and only 1-2% additional weights in the form of low-rank matrix perturbations are trained.
For maximum efficiency it is recommended to use a... See more
mistral-finetune is a light-weight codebase that enables memory-efficient and performant finetuning of Mistral's models. It is based on LoRA, a training paradigm where most weights are frozen and only 1-2% additional weights in the form of low-rank matrix perturbations are trained.
For maximum efficiency it is recommended to use a... See more
GitHub - mistralai/mistral-finetune
LLM-PowerHouse: A Curated Guide for Large Language Models with Custom Training and Inferencing
Welcome to LLM-PowerHouse, your ultimate resource for unleashing the full potential of Large Language Models (LLMs) with custom training and inferencing. This GitHub repository is a comprehensive and curated guide designed to empower developers,... See more
Welcome to LLM-PowerHouse, your ultimate resource for unleashing the full potential of Large Language Models (LLMs) with custom training and inferencing. This GitHub repository is a comprehensive and curated guide designed to empower developers,... See more
ghimiresunil • GitHub - ghimiresunil/LLM-PowerHouse-A-Curated-Guide-for-Large-Language-Models-with-Custom-Training-and-Inferencing: LLM-PowerHouse: Unleash LLMs' potential through curated tutorials, best practices, and ready-to-use code for custom training and inferencing.
LLMs and LLM Training
Build & Deployments
Our build process starts by pushing changes to a repository on GitHub. When code is pushed to a repository through a pull request, it triggers a job to build the changes made to the branch and deploy them in isolation. This worklow happens interactively within the pull request, where the author has visibility of all steps.
Some... See more
Our build process starts by pushing changes to a repository on GitHub. When code is pushed to a repository through a pull request, it triggers a job to build the changes made to the branch and deploy them in isolation. This worklow happens interactively within the pull request, where the author has visibility of all steps.
Some... See more
How we approach CI/CD · Resend
Almost every company I talk to, and basically every solution vendor, has been pushing for people to use AI to “talk-to-your-data,” an approach allows the AI to retrieve content from a company’s proprietary databases and then work with the documents and data it retrieves. The problem is that AIs hallucinate, or make up plausible information, all the... See more
Ethan Mollick • Almost an Agent: What GPTs can do
- ClickHouse: It's a high performance columnar database that's great for real time queries. It enables querying and storing large amounts of data on commodity hardware. Some of my customers have millions of page views and I don't have an unlimited budget, so it's been very handy.
- PostgreSQL: My favorite database. Sane defaults, battle-tested, and well
The Tech Stack of a One-Man SaaS
The Knowledge Graph enables you to search for things, people or places that Google knows about—landmarks, celebrities, cities, sports teams, buildings, geographical features, movies, celestial objects, works of art and more—and instantly get information that’s relevant to your query. This is a critical first step towards building the next... See more
Amit Singhal • Introducing the Knowledge Graph: things, not strings
When a test fails, you should be able to begin investigation with nothing more than the test’s name and its failure messages —no need to add more information and rerun the test.
Effective use of unit test frameworks and assertion libraries (JUnit, Truth, pytest, GoogleTest, etc.) serves two important purposes. Firstly, the more precisely we express... See more
Effective use of unit test frameworks and assertion libraries (JUnit, Truth, pytest, GoogleTest, etc.) serves two important purposes. Firstly, the more precisely we express... See more