GitHub - BrunoScaglione/langtest: Deliver safe & effective language models

2-5x faster 50% less memory local LLM finetuning

• Manual autograd engine - hand derived backprop steps.


• 2x to 5x faster than QLoRA. 50% less memory usage.


• All kernels written in OpenAI's Triton language.


• 0% loss in accuracy - no approximation methods - all exact.


• No change of hardware necessary. Supports NVIDIA GPUs since 2018+. Minimum CUDA Compute Cap

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HoneyHive is a collaboration platform to test and evaluate, monitor and debug your LLM apps, from prototype to production. It enables you to continuously improve LLM apps in production with human feedback, quantitative rigour and safety best-practices.

GPT4All: An ecosystem of open-source on-edge large language models.

Important

GPT4All v2.5.0 and newer only supports models in GGUF format (.gguf). Models used with a previous version of GPT4All (.bin extension) will no longer work.

GPT4All is an ecosystem to run powerful and customized large language models that work locally on consumer grade CPUs a... See more

SGLang is a structured generation language designed for large language models (LLMs). It makes your interaction with LLMs faster and more controllable by co-designing the frontend language and the runtime system.

The core features of SGLang include:

• A Flexible Front-End Language : This allows for easy programming of LLM applications with multiple ch

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