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Creating safe artificial general intelligence that benefits all of humanity. Our work to create safe and beneficial AI requires a deep understanding of the potential risks and benefits, as well as careful consideration of the impact. | It is an open platform for operating large language models (LLMs) in production. Fine-tune, serve, deploy, and monitor any LLMs with ease. Run inference with any open-source large-language models, deploy to the cloud or on-premise, and build powerful AI apps. |
Pioneering research on the path to AGI;
Transforming work and creativity with AI | State-of-the-art LLMs;
Flexible APIs;
Freedom to build;
Streamline deployment;
Bring your own LLM |
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GitHub Stars - | GitHub Stars 11.9K |
GitHub Forks - | GitHub Forks 786 |
Stacks 932 | Stacks 3 |
Followers 194 | Followers 9 |
Votes 0 | Votes 0 |
Integrations | |

It is the base model weights and network architecture of Grok-1, the large language model. Grok-1 is a 314 billion parameter Mixture-of-Experts model trained from scratch by xAI.

That transforms AI-generated content into natural, undetectable human-like writing. Bypass AI detection systems with intelligent text humanization technology

It is a framework built around LLMs. It can be used for chatbots, generative question-answering, summarization, and much more. The core idea of the library is that we can “chain” together different components to create more advanced use cases around LLMs.

It is Google’s largest and most capable AI model. It is built to be multimodal, it can generalize, understand, operate across, and combine different types of info — like text, images, audio, video, and code.

It allows you to run open-source large language models, such as Llama 2, locally.

It is a state-of-the-art foundational large language model designed to help researchers advance their work in this subfield of AI.

It is a project that provides a central interface to connect your LLMs with external data. It offers you a comprehensive toolset trading off cost and performance.

It is a general-purpose speech recognition model. It is trained on a large dataset of diverse audio and is also a multi-task model that can perform multilingual speech recognition as well as speech translation and language identification.

It is a library for building stateful, multi-actor applications with LLMs, built on top of (and intended to be used with) LangChain. It extends the LangChain Expression Language with the ability to coordinate multiple chains (or actors) across multiple steps of computation in a cyclic manner.

It is a platform for building production-grade LLM applications. It lets you debug, test, evaluate, and monitor chains and intelligent agents built on any LLM framework and seamlessly integrates with LangChain, the go-to open source framework for building with LLMs.