Ognoexperiment27multi_verse_modelCalmexperiment-7B-GGUF

MaziyarPanahi/Ognoexperiment27multi_verse_modelCalmexperiment-7B-GGUF

• Model creator: automerger
• Original model: automerger/Ognoexperiment27multi_verse_modelCalmexperiment-7B

Description

MaziyarPanahi/Ognoexperiment27multi_verse_modelCalmexperiment-7B-GGUF contains GGUF format model files for automerger/Ognoexperiment27multi_verse_modelCalmexperiment-7B.

About GGUF

GGUF is a new format introduced by the llama.cpp team on August 21st 2023. It is a replacement for GGML, which is no longer supported by llama.cpp.

Here is an incomplete list of clients and libraries that are known to support GGUF:

• llama.cpp. The source project for GGUF. Offers a CLI and a server option.
• llama-cpp-python, a Python library with GPU accel, LangChain support, and OpenAI-compatible API server.
• LM Studio, an easy-to-use and powerful local GUI for Windows and macOS (Silicon), with GPU acceleration. Linux available, in beta as of 27/11/2023.
• text-generation-webui, the most widely used web UI, with many features and powerful extensions. Supports GPU acceleration.
• KoboldCpp, a fully featured web UI, with GPU accel across all platforms and GPU architectures. Especially good for story telling.
• GPT4All, a free and open source local running GUI, supporting Windows, Linux and macOS with full GPU accel.
• LoLLMS Web UI, a great web UI with many interesting and unique features, including a full model library for easy model selection.
• Faraday.dev, an attractive and easy to use character-based chat GUI for Windows and macOS (both Silicon and Intel), with GPU acceleration.
• candle, a Rust ML framework with a focus on performance, including GPU support, and ease of use.
• ctransformers, a Python library with GPU accel, LangChain support, and OpenAI-compatible AI server. Note, as of time of writing (November 27th 2023), ctransformers has not been updated in a long time and does not support many recent models.

Special thanks

🙏 Special thanks to Georgi Gerganov and the whole team working on llama.cpp for making all of this possible.