README.md

---
license: apache-2.0
language:
- en
tags:
- creative
- creative writing
- fiction writing
- plot generation
- sub-plot generation
- fiction writing
- story generation
- scene continue
- storytelling
- fiction story
- science fiction
- romance
- all genres
- story
- writing
- vivid prosing
- vivid writing
- fiction
- roleplaying
- bfloat16
- swearing
- rp
- horror
- mistral nemo
- mergekit
pipeline_tag: text-generation
---

( quants uploading... Imatrix examples to be posted ; link to main repo non-imatrix quants with examples below )

<h2>L3-Dark-Planet-8B-NEO-Imatrix-GGUF</h2>

<img src="dark-planet.jpg" style="float:right; width:300px; height:300px; padding:10px;">

It is a LLama3 model, max context of 8192 (or 32k+ with rope).

This model has been designed to be relatively bullet proof and operates with all parameters, including temp settings from 0 to 5.

It is an extraordinary compressed model, with a very low perplexity level (lower than Meta Llama3 Instruct).

It is for any writing, fiction or roleplay activity.

It requires Llama3 template and/or "Command-R" template.

This repo has the NEO Imatrix quants for model (reg quants repo): 

[ https://huggingface.co/DavidAU/L3-Dark-Planet-8B-GGUF ] 

Example outputs below.

<B>Model Notes:</B>

- Detail, prose and fiction writing abilities are significantly increased vs L3 Instruct.
- For more varied prose (sentence/paragraph/dialog) raise the temp and/or add more instructions in your prompt(s).
- Role-players: Careful raising temp too high as it may affect instruction following.
- This model works with rep pen of 1 or higher, 1.05+ recommended.
- If you want a specific type of prose (IE horror) add in "(vivid horror)" or "(graphic vivid horror)" (no quotes) in your prompt(s).
- A lot of GPTisms have been removed. There are still a few however - errrrr.
- This is not a "happy ever after" model. It has a negative bias.
- Output length will vary however this model prefers shortly outputs unless you state the size.
- For creative uses, different quants will produce slightly different output.
- Due to the high stability and compressed nature of this model, all quants will operate at above average levels.
- If you use rope to extend context, increase temp AND instructions detail levels to compensate for "rope issues".
- Source code for this model (Bfloat16), Float 32 master GGUFs (and source), and Imatrix GGUFs versions will be uploaded shortly at separate repos.

Note the "float32" version of this model behaves VERY differently which is why it was not uploaded first. Usually I would
use the "float32" version only, however the "character range" displayed by the Bfloat16 and Float32 versions of this model
dictate they have their own repos.

The Imatrix versions of this model have even lower perplexity (1/2 level of magnitude lower than this model, 1 full level of magnitude 
lower than LLama3 Instruct) then both this model and Llama3 Instruct and enhanced output.

This is a LLAMA3 model, and requires Llama3 template, but may work with other template(s) and has maximum context of 8k / 8192. 
However this can be extended using "rope" settings up to 32k.

If you use "Command-R" template your output will be very different from using "Llama3" template.

Here is the standard LLAMA3 template:

<PRE>
{
  "name": "Llama 3",
  "inference_params": {
    "input_prefix": "<|start_header_id|>user<|end_header_id|>\n\n",
    "input_suffix": "<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n",
    "pre_prompt": "You are a helpful, smart, kind, and efficient AI assistant. You always fulfill the user's requests to the best of your ability.",
    "pre_prompt_prefix": "<|start_header_id|>system<|end_header_id|>\n\n",
    "pre_prompt_suffix": "<|eot_id|>",
    "antiprompt": [
      "<|start_header_id|>",
      "<|eot_id|>"
    ]
  }
}
</PRE>

<b>Optional Enhancement:</B>

The following can be used in place of the "system prompt" or "system role" to further enhance the model.

It can also be used at the START of a NEW chat, but you must make sure it is "kept" as the chat moves along.
In this case the enhancements do not have as strong effect at using "system prompt" or "system role".

Copy and paste EXACTLY as noted, DO NOT line wrap or break the lines, maintain the carriage returns exactly as presented.

<PRE>
Below is an instruction that describes a task. Ponder each user instruction carefully, and use your skillsets and critical instructions to complete the task to the best of your abilities.

Here are your skillsets:
[MASTERSTORY]:NarrStrct(StryPlnng,Strbd,ScnSttng,Exps,Dlg,Pc)-CharDvlp(ChrctrCrt,ChrctrArcs,Mtvtn,Bckstry,Rltnshps,Dlg*)-PltDvlp(StryArcs,PltTwsts,Sspns,Fshdwng,Climx,Rsltn)-ConfResl(Antg,Obstcls,Rsltns,Cnsqncs,Thms,Symblsm)-EmotImpct(Empt,Tn,Md,Atmsphr,Imgry,Symblsm)-Delvry(Prfrmnc,VcActng,PblcSpkng,StgPrsnc,AudncEngmnt,Imprv)

[*DialogWrt]:(1a-CharDvlp-1a.1-Backgrnd-1a.2-Personality-1a.3-GoalMotiv)>2(2a-StoryStruc-2a.1-PlotPnt-2a.2-Conflict-2a.3-Resolution)>3(3a-DialogTech-3a.1-ShowDontTell-3a.2-Subtext-3a.3-VoiceTone-3a.4-Pacing-3a.5-VisualDescrip)>4(4a-DialogEdit-4a.1-ReadAloud-4a.2-Feedback-4a.3-Revision)

Here are your critical instructions:
Ponder each word choice carefully to present as vivid and emotional journey as is possible. Choose verbs and nouns that are both emotional and full of imagery. Load the story with the 5 senses. Aim for 50% dialog, 25% narration, 15% body language and 10% thoughts. Your goal is to put the reader in the story.
</PRE>

You do not need to use this, it is only presented as an additional enhancement which seems to help scene generation
and scene continue functions.

This enhancement WAS NOT used to generate the examples below.

<h3>EXAMPLES PROMPTS and OUTPUT:</h3>

Examples are created using quant Q4_K_M, "temp=.8" (unless otherwise stated), minimal parameters and "LLAMA3" template. 

Model has been tested with "temp" from ".1" to "5".

Below are the least creative outputs, prompt is in <B>BOLD</B>.

---

<B><font color="red">WARNING:</font> NSFW. Vivid prose. Visceral Details. Violence. HORROR. Swearing. UNCENSORED. </B>

---

Imatrix NEO generation examples to be posted shortly...