Nicolay Gerold
@nicolaygerold
Nicolay Gerold
DeepSeek Coder comprises a series of code language models trained from scratch on both 87% code and 13% natural language in English and Chinese, with each model pre-trained on 2T tokens. We provide various sizes of the code model, ranging from 1B to 33B versions. Each model is pre-trained on repo-level code corpus by employing a window size of 16K... See more
DeepSeek Coder
The context size of the input is too small for when you want to analyse CSV's with 1000's of rows and embedding doesn't really work because it loses context.
r/LLMDevs - Reddit
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.
Discord - A New Way to Chat with Friends & Communities
- UUID Version 1 (v1) is generated from timestamp, monotonic counter, and a MAC address.
- UUID Version 2 (v2) is reserved for security IDs with no known details2.
- UUID Version 3 (v3) is generated from MD5 hashes of some data you provide. The RFC suggests DNS and URLs among the candidates for data.
- UUID Version 4 (v4) is generated from entirely random
nicole@web • TIL: 8 versions of UUID and when to use them | nicole@web
Data-Juicer: A One-Stop Data Processing System for Large Language Models
Data-Juicer is a one-stop data processing system to make data higher-quality, juicier, and more digestible for LLMs. This project is being actively updated and maintained, and we will periodically enhance and add more features and data recipes. We welcome you to join us in... See more
Data-Juicer is a one-stop data processing system to make data higher-quality, juicier, and more digestible for LLMs. This project is being actively updated and maintained, and we will periodically enhance and add more features and data recipes. We welcome you to join us in... See more
alibaba • GitHub - alibaba/data-juicer: A one-stop data processing system to make data higher-quality, juicier, and more digestible for LLMs! 🍎 🍋 🌽 ➡️ ➡️🍸 🍹 🍷为大语言模型提供更高质量、更丰富、更易”消化“的数据！
Super JSON Mode is a Python framework that enables the efficient creation of structured output from an LLM by breaking up a target schema into atomic components and then performing generations in parallel.
It supports both state of the art LLMs via OpenAI 's legacy completions API and open source LLMs such as via Hugging Face Transformers and vLLM .... See more
It supports both state of the art LLMs via OpenAI 's legacy completions API and open source LLMs such as via Hugging Face Transformers and vLLM .... See more
varunshenoy • GitHub - varunshenoy/super-json-mode: Low latency JSON generation using LLMs ⚡️
- You have access to a proprietary asset (like data) that others don’t have easy access to. In our “write job postings” example, perhaps you have a corpus of thousands of job postings including some outcome scores (as to how well they did). You could use this data to create better job postings. Others don’t have ready access to this data. Note: The
Dharmesh Shah • How To Build a Defensible A.I. Startup
Protecting LLM products:
(1) Is hard to bootstrap. This already hints to existing customers or you need to get a bunch of your customers to co-develop (insurance model → companies pooling their data to solve a problem they all have). This runs into a bunch of issues: competitive drive of the companies, data privacy and security.
(2) Reserved for existing companies. This is the co-pilot model.
(3) This might be the most sustainable one, but it is also the hardest one. I have not seen anything in that direction yet besides OpenAI.
factory_boy
factory_boy is a fixtures replacement based on thoughtbot's factory_bot.
As a fixtures replacement tool, it aims to replace static, hard to maintain fixtures with easy-to-use factories for complex objects.
Instead of building an exhaustive test setup with every possible combination of corner cases, factory_boy allows you to use objects... See more
factory_boy is a fixtures replacement based on thoughtbot's factory_bot.
As a fixtures replacement tool, it aims to replace static, hard to maintain fixtures with easy-to-use factories for complex objects.
Instead of building an exhaustive test setup with every possible combination of corner cases, factory_boy allows you to use objects... See more
FactoryBoy • GitHub - FactoryBoy/factory_boy: A test fixtures replacement for Python
API wrappers, general-purpose AI tools and third-party AI tools for big platforms.
API wrappers have a weak moat.
General AI tools try to be the jack-of-all-trades.
Big platforms will eat up small apps by adding similar AI features themselves.
API wrappers have a weak moat.
General AI tools try to be the jack-of-all-trades.
Big platforms will eat up small apps by adding similar AI features themselves.