GitHub - jmorganca/ollama: Get up and running with Llama 2 and other large language models locally
Original creator : Jesse Zhang (GH: emptycrown, Twitter: @thejessezhang), who courteously donated the repo to LlamaIndex!
This is a simple library of all the data loaders / readers / tools / llama-packs that have been created by the community. The goal is to make it extremely easy to connect large language models to a large variety of knowledge sour... See more
This is a simple library of all the data loaders / readers / tools / llama-packs that have been created by the community. The goal is to make it extremely easy to connect large language models to a large variety of knowledge sour... See more
GitHub - run-llama/llama-hub: A library of data loaders for LLMs made by the community -- to be used with LlamaIndex and/or LangChain
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
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
nomic-ai • GitHub - nomic-ai/gpt4all: gpt4all: open-source LLM chatbots that you can run anywhere
TL;DR
LLMLingua utilizes a compact, well-trained language model (e.g., GPT2-small, LLaMA-7B) to identify and remove non-essential tokens in prompts. This approach enables efficient inference with large language models (LLMs), achieving up to 20x compression with minimal performance loss.
... See more
LLMLingua utilizes a compact, well-trained language model (e.g., GPT2-small, LLaMA-7B) to identify and remove non-essential tokens in prompts. This approach enables efficient inference with large language models (LLMs), achieving up to 20x compression with minimal performance loss.
... See more
microsoft • GitHub - microsoft/LLMLingua: To speed up LLMs' inference and enhance LLM's perceive of key information, compress the prompt and KV-Cache, which achieves up to 20x compression with minimal performance loss.
GitHub - MadcowD/ell: A language model programming library.
github.com