How this analysis was created: This summary and feature list were written by an AI model that read the project's README and public documentation pages. Each feature links to the documentation it came from; stars, license and language come straight from the GitHub API. The model does not read the source code, and the analysis is refreshed when the project is re-analysed. Learn more on our About page.
MultimodalC4 is a multimodal extension of c4 that interleaves millions of images with text.
The main features of allenai/mmc4 are: Large Language Models, Natural Language Processing.
Open-source alternatives to allenai/mmc4 include: artidoro/qlora — This project is a quantized fine-tuning framework for large language models. It implements a low-rank adaptation… cranot/chatbot-injections-exploits — ChatBot Injection and Exploit Examples: A Curated List of Prompt Engineer Commands - ChatGPT. aigc-audio/audiogpt — AudioGPT is an LLM-driven audio framework and processing suite that uses large language models to orchestrate neural… alisawuffles/ambient — Code and data associated with the AmbiEnt dataset in "We're Afraid Language Models Aren't Modeling Ambiguity" (Liu et… berriai/litellm — LiteLLM is a unified gateway and proxy server designed to centralize access to over one hundred language model… deep-floyd/if — IF is a text-to-image diffusion system that translates natural language descriptions into visual imagery. The project…
Code and data associated with the AmbiEnt dataset in "We're Afraid Language Models Aren't Modeling Ambiguity" (Liu et al., 2023)
This project is a quantized fine-tuning framework for large language models. It implements a low-rank adaptation library and a four-bit quantizer to reduce the GPU memory requirements needed to train large models. The framework utilizes four-bit quantization and low-rank adapters to enable model training on consumer-grade hardware. It further reduces the memory footprint through double quantization and a paged optimizer that offloads states to system RAM. The system supports distributed training across multiple GPUs to handle larger parameter scales and includes utilities for custom dataset
AudioGPT is an LLM-driven audio framework and processing suite that uses large language models to orchestrate neural audio pipelines. It functions as a multimodal audio generator and processing system, integrating a collection of pretrained models to handle speech synthesis, sound generation, and audio manipulation. The system is distinguished by its ability to generate audio from diverse inputs, including text and images, and its capacity to produce synchronized talking head videos. It also operates as a neural speech translator, converting spoken language between different tongues while pre
LiteLLM is a unified gateway and proxy server designed to centralize access to over one hundred language model providers. It provides a standardized API interface that abstracts vendor-specific schemas, allowing developers to interact with diverse models through a single, consistent format. By acting as a central traffic management layer, it enables organizations to route, secure, and govern model interactions across multiple deployments. The platform distinguishes itself through its policy-driven architecture, which uses configuration-based routing to manage traffic distribution, load balanc