Nicolay Gerold

Here's a list of those log levels from lowest precedence to highest:

notset (0) - Indicates that ancestor loggers should be consulted for the log level or that all events are logged (default setting)

debug (10) - Detailed information that would be of interest to the developer for diagnostic purposes

info (20) - Information that confirms that your appl... See more

Langfuse is an open source observability & analytics solution for LLM-based applications. It is mostly geared towards production usage but some users also use it for local development of their LLM applications.

Langfuse is focused on applications built on top of LLMs. Many new abstractions and common best practices evolved recently, e.g. agents,... See more

One Explorer. All Your Files.

Unify files from all your devices and clouds into a single, easy-to-use explorer.

Designed for creators, hoarders and the painfully disorganized.

Overview¶

Ballista is a distributed compute platform primarily implemented in Rust, and powered by Apache Arrow.

Ballista has a scheduler and an executor process that are standard Rust executables and can be executed directly, but Dockerfiles are provided to build images for use in containerized environments, such as Docker, Docker Compose, and Kube... See more

For any conversational use case, such as chatbots, we need conversational memory. The idea behind conversational memory is simple: rather than sending just the most recent interaction to our LLM, we send a history of interactions + the most recent interaction to our LLM — typically in a chat log style format.

With and without conversational memory.

D... See more

Trying to get a better understanding of how prompts work in relation to fine-tunes, and trying to see if any of them are actually reliable enough to be used in a "production" type environment.

My end goals are basically

• A reliable AI assistant that I know is safe, secure and private. Any information about myself, my household or my proprietary ideas

... See more

am using my own hardware at home to infer, train, and fine-tune (or trying to; my training efforts have been pretty disasterous so far, but inference works very well).

My current uses of LLM inference are:

• Asking questions of a RAG system backed by a locally indexed Wikipedia dump, mainly with Marx-3B and PuddleJumper-13B-v2,


• Code co-pilot with Rift-C

... See more

multimodal-maestro

👋 hello

Multimodal-Maestro gives you more control over large multimodal models to get the outputs you want. With more effective prompting tactics, you can get multimodal models to do tasks you didn't know (or think!) were possible. Curious how it works? Try our HF space!

HelixNet is a Deep Learning architecture consisting of 3 x Mistral-7B LLMs. It has an actor, a critic, and a regenerator. The actor LLM produces an initial response to a given system-context and a question. The critic then takes in as input, a tuple of (system-context, question, response) and provides a critique based on the provided answer to the ... See more