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Llama-3-70b-Uncensored-Lumi-Tess-gradient-GGUF

HF 源站

backyardai/Llama-3-70b-Uncensored-Lumi-Tess-gradient-GGUF is an uncensored open-source model hosted on Hugging Face.

GGUF70Buncencoredllama-3tesslumimaidLumi-tessimatrixconversational
README.md说明 / 使用方法

tags:

  • uncencored
  • llama-3
  • tess
  • lumimaid
  • Lumi-tess base_model: ryzen88/Llama-3-70b-Uncensored-Lumi-Tess-gradient model_name: Llama-3-70b-Uncensored-Lumi-Tess-gradient-GGUF quantized_by: brooketh parameter_count: 70553706496

The official library of GGUF format models for use in the local AI chat app, Backyard AI.


Llama 3 Uncensored Lumi Tess Gradient 70B

  • Creator: ryzen88
  • Original: Llama 3 Uncensored Lumi Tess Gradient 70B
  • Date Created: 2024-05-10
  • Trained Context: 262144 tokens
  • Description: Good Llama3 uncensored model with a long context, made using a breadcrumb ties merger of Instruct-gradient, Lumimaid, and Tess models. Works with a very wide range of sampler settings.

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

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来源与版本

作者
backyardai
最近更新
2024/06/07
最新创建
2024/06/07
HF 趋势
未知
数据快照
2026/09/16
版本
未知
许可证
unknown