DarkSapling-V2-Ultra-Quality-7B-GGUF Open-Source Model - Ultra-High-Quality Text Processing with 32k Context

Darksapling V2 Ultra Quality 7B GGUF

Developed by DavidAU

A version completely remerged and remade based on the Dark Sapling V2 7B model, with a 32k context length, featuring ultra-high quality and 32-bit improvement

Large Language Model EnglishOpen Source License:Apache-2.0 #32k long text generation #High-precision quantization #Creative writing optimization

Downloads 385

Release Time : 6/4/2024

Model Overview

A large language model focused on creative writing, role-playing, and story creation, excelling in instruction following, reasoning, and emotional expression

Model Features

32k ultra-long context

Supports a context window of 32k length, suitable for handling long texts and complex scenarios

Quantization performance improvement

Significant performance improvement under Q4KM quantization, reaching the level of Q6 in operation, with obvious improvements in all quantization versions

Subtle understanding ability

Can better understand the subtle differences and emotional expressions in the text, reducing the need for prompt words

32-bit precision improvement

Adopts 32-bit precision improvement technology to improve the output quality of the model

Model Capabilities

Creative writing

Role-playing

Story creation

Instruction following

Emotional expression

Complex reasoning

Use Cases

Creative writing

Novel creation

Generate coherent long-story content

Can produce texts rich in creativity and emotional depth

Poetry creation

Generate poems with rhythm and emotional expression

Can capture subtle emotions and artistic expressions

Role-playing

Character dialogue

Maintain character consistency in long-term conversations

Can maintain character characteristics and conversation coherence

Scene construction

Create detailed role-playing scenarios

Can build rich situations and interactions

🚀 Dark Sapling V2 7B - 32k Context - Ultra Quality - 32bit upscale

Complete remerge and remaster of the incredible Dark Sapling V2 7B - 32k Context from source files, offering superior performance in text generation.

Dark Sapling

✨ Features

Quantization Improvement: Registering an impressive drop of 320 points (lower is better) at Q4KM. This puts "Q4KM" operating at "Q6" levels, and further elevates Q6 and Q8 as well. Even Q2K (smallest quant) will operate at much higher levels than its original source counterpart.
Enhanced Performance: Superior performance in instruction following, reasoning, depth, nuance, and emotion.
Prompt Size Reduction: Reduction in prompt size as it understands nuance better, resulting in more context available for output.
Quant Difference: There will be an outsized difference between quants, especially for creative and/or "no right answer" use cases.

📚 Documentation

Results

The result is superior performance in instruction following, reasoning, depth, nuance, and emotion. There is a reduction in prompt size as it understands nuance better, and as a side effect, more context is available for output due to the reduction in prompt size.

Quantization Suggestion

Note that there will be an outsized difference between quants, especially for creative and/or "no right answer" use cases. Because of this, it is suggested to download the highest quant you can operate, and its closest neighbours. For example, Q4KS, Q4KM, Q5KS.

Other Information

Imatrix Plus versions will be uploaded to a separate repo shortly.
Special thanks to "TEEZEE" the original model creator: [ https://huggingface.co/TeeZee/DarkSapling-7B-v2.0 ]
Note that Version 1 and Version 1.1 are also remastered.

Highest Quality Settings / Optimal Operation Guide / Parameters and Samplers

This is a "Class 1". For all settings used for this model (including specifics for its "class"), including example generation(s) and for advanced settings guide (which many times addresses any model issue(s)), including methods to improve model performance for all use case(s) as well as chat, roleplay, and other use case(s) please see: [ https://huggingface.co/DavidAU/Maximizing-Model-Performance-All-Quants-Types-And-Full-Precision-by-Samplers_Parameters ]

📄 License

This project is licensed under the Apache-2.0 license.

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