--- language: - en license: apache-2.0 tags: - 32 bit upscale - full 32 bit precision - master files base_model: DavidAU/Psyonic-Cetacean-V1-20B-Ultra-Quality-Float32 model_name: Psyonic-Cetacean-V1-20B-Ultra-Quality-GGUF quantized_by: brooketh parameter_count: 19994362880 --- **
The official library of GGUF format models for use in the local AI chat app, Backyard AI.
** *** # Psyonic Cetacean V1 Ultra Quality 20B - **Creator:** [DavidAU](https://huggingface.co/DavidAU/) - **Original:** [Psyonic Cetacean V1 Ultra Quality 20B](https://huggingface.co/DavidAU/Psyonic-Cetacean-V1-20B-Ultra-Quality-Float32) - **Date Created:** 2024-06-01 - **Trained Context:** 4096 tokens - **Description:** The one and only Space Whale, remastered and requantized in full 32-bit precision. Should be a dramatic improvement over the classic Psyonic Cetacean 20B in terms of creativity and quality of inference. *** ## What is a GGUF? GGUF is a large language model (LLM) format that can be split between CPU and GPU. GGUFs are compatible with applications based on llama.cpp, such as Backyard AI. Where other model formats require higher end GPUs with ample VRAM, GGUFs can be efficiently run on a wider variety of hardware. GGUF models are quantized to reduce resource usage, with a tradeoff of reduced coherence at lower quantizations. Quantization reduces the precision of the model weights by changing the number of bits used for each weight. *** ## Backyard AI - Free, local AI chat application. - One-click installation on Mac and PC. - Automatically use GPU for maximum speed. - Built-in model manager. - High-quality character hub. - Zero-config desktop-to-mobile tethering. Backyard AI makes it easy to start chatting with AI using your own characters or one of the many found in the built-in character hub. The model manager helps you find the latest and greatest models without worrying about whether it's the correct format. Backyard AI supports advanced features such as lorebooks, author's note, text formatting, custom context size, sampler settings, grammars, local TTS, cloud inference, and tethering, all implemented in a way that is straightforward and reliable. **Join us on [Discord](https://discord.gg/SyNN2vC9tQ)** ***