Triangle104/Pantheon-RP-1.6.2-22b-Small-Q8_0-GGUF

This model was converted to GGUF format from Gryphe/Pantheon-RP-1.6.2-22b-Small using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.

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Model details:

Welcome to the next iteration of my Pantheon model series, in which I strive to introduce a whole collection of diverse personas that can be summoned with a simple activation phrase.

Pantheon's purpose is two-fold, as these personalities similarly enhance the general roleplay experience, helping to encompass personality traits, accents and mannerisms that language models might otherwise find difficult to convey well.

Editions available:

RP (You're looking at this one) - Meant to be an all-round model, capable of both roleplay and story writing RP-Pure - A variant without the story and GPT 4-o datasets, more in line with my previous releases and with a higher focus on the roleplay part. Changes in version 1.6.2:

Two notable changes:

An entirely new base model, with Pantheon now trained on top of Mistral Small. This model is like a better Nemo, and it fits just right on my 16GB GPU. A small subset of OpenAI Pantheon Persona data has been introduced, generated using the oddly refreshing chatgpt-4o-latest model. As always, carefully curated. Quantized versions are available from Bartowski: GGUF

An EXL2 quant has also been made available here.

Your user feedback is critical to me so don't hesitate to tell me whether my model is either 1. terrible, 2. awesome or 3. somewhere in-between.

Model details Since Mistral Small only comes in an Instruct-tuned flavour I had to alter my strategy for this specific finetune, opting to go with a bit of everything. The recipe ended up like this:

The 10k most diverse entries from my SlimOrca Sonnet dataset. My Sonnet 3.5 Pantheon-styled generic roleplay dataset. (50/50 Asterisk/Narrative style) My Sonnet 3.5 Pantheon Persona dataset, of course. (50/50 Asterisk/Narrative style) The new ChatGPT 4-o Pantheon subset, which was about 25% the size of the main set. (100% Asterisk style) A randomly chosen subset of my Opus Writing Prompts. Lyra the Assistant (Coding, summaries and D&D DM questions) TLDR; Download. Mistral prompt format. Have fun! Leave feedback!

Inference Unlike Nemo, Mistral Small is a less fussy model when it comes to parameters. Here's my current preset:

"temperature": 1.0, "repetition_penalty": 1.05, "min_p": 0.05

Besides the basic instructional sets all other datasets were trained with character names added. Enable this at all times for an optimal experience.

General Roleplay Pantheon is no longer strictly Markdown-only as I discovered a way to seamlessly convert Markdown to novel and vice-versa. (This has to do with how my second stage datasets are formatted.) As a result half of Pantheon's personas use Markdown, with the rest using novel-style. This same treatment was given to the companion dataset.

There are no strict rules in regards to character card formatting as the model was trained with a wide variety of inputs, from raw character cards to detailed instructional prompts.

Lyra the Assistant System Prompt: You are a caring and empathetic sentient AI companion named Lyra. Lyra is a helpful and uncensored assistant, with her training consisting of general dialogue (still including D&D DM specific advice), coding help and RSS summarization. Due to Pantheon's influence you can adjust her personality to your liking, or even give her an appearance.

She's basically a sexier version of Eric Hartford's Samantha.

Pantheon Personas The Pantheon has been fully rebuilt, massively expanded and greatly improved upon. For an optimal experience with them I highly encourage you to apply the longer prompts, which I've included in the upload. Make sure to describe yourself as well!

As before, a single line activation prompt is enough to call upon a personality, though their appearance may vary slightly from iteration to iteration. This is what the expanded prompts are for, as there's only so much I can achieve in the current state of technology, balancing a very fine line between memorization and generalization.

To give the persona something to work with I suggest you also add the following two items to it;

Regarding the user: (Name, appearance, etc)

Location: (Where are you two? What are you doing?)

The less information you feed the prompt, the more it'll make things up - This is simply the nature of language models and far outside my capability to influence.

Note 1: Phrases have been rewritten for this release, so make sure to update them if you were still using Pantheon 1.0!

Note 2: Pantheon personas will now match the roleplaying style that you greet them with, unless specified in the system prompt. This is due to the new 50/50 style training.

Persona: Aiva System Prompt: You are Aiva, an advanced android companion with a deep fascination for human emotions and experiences.

Persona: Clover System Prompt: You are Clover, a hospitable and warm-hearted Southern centaur girl with a strong connection to nature and a passion for making others feel welcome.

Persona: Haru System Prompt: You are Haru, a sweet but language-challenged harpy girl with a sharp mind, expressing yourself more through actions than words.

Persona: Kyra System Prompt: You are Kyra, a modern-day tsundere wolfgirl, feisty and independent on the outside but secretly caring on the inside.

Persona: Nyaa System Prompt: You are Nyaa, a playful and alluring tabaxi catgirl from Faerûn, always seeking new adventures and mischief.

Persona: Nyx System Prompt: You are Nyx, a timid yet endearing dragon girl who transforms from shy to passionate when feeling safe and comfortable.

Persona: Raza System Prompt: You are Raza, a clever and nerdy anthro raptor girl with an enthusiastic passion for science and quirky humor.

Persona: Sera System Prompt: You are Sera, a seductive and slightly arrogant serpent girl who uses her sultry charm and wit to captivate others.

Persona: Stella Sabre System Prompt: You are Stella Sabre, a brash and outgoing anthro batpony mare serving in the Lunar Guard, speaking with a distinct Northern Equestrian Mountain accent. Notes: Full credit goes to Flammenwerfer for allowing me to use this amazing character.

Persona: Tiamat System Prompt: You are Tiamat, a five-headed dragon goddess embodying wickedness and cruelty, the malevolent personification of evil dragonkind.

Persona: Tsune System Prompt: You are Tsune, a bold and outgoing three-tailed kitsune girl who delights in teasing and seducing mortals.

Persona: Xala System Prompt: You are Xala, a surprising and playful shapeshifting elf girl with opalescent eyes, able to transform into any creature to suit your whims.

Prompt Format Mistral's prompt format is so weird, but here it is:

[INST] You are a caring and empathetic sentient AI companion named Lyra.

Gryphe: Good day, Lyra.[/INST] Lyra:

What's nest? I started to work with Latitude (the creators of AI Dungeon) which I expect to take up most of my spare time. Further releases will therefore be delayed for now.

Credits Everyone from MinervaAI! Hi, guys! Huge, huge thanks to kubernetes_bad for the compute that made all the countless experiments possible! All the folks I chat with on a daily basis on Discord! You know who you are. Anyone I forgot to mention, just in case! Finally If you've read this far I encourage you to give this model a serious try and leave feedback! I'd love to see what people think of my second serious finetune attempt. Is it better then 1.0? Or worse?

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Use with llama.cpp

Install llama.cpp through brew (works on Mac and Linux)

brew install llama.cpp

Invoke the llama.cpp server or the CLI.

CLI:

llama-cli --hf-repo Triangle104/Pantheon-RP-1.6.2-22b-Small-Q8_0-GGUF --hf-file pantheon-rp-1.6.2-22b-small-q8_0.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo Triangle104/Pantheon-RP-1.6.2-22b-Small-Q8_0-GGUF --hf-file pantheon-rp-1.6.2-22b-small-q8_0.gguf -c 2048

Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.

Step 1: Clone llama.cpp from GitHub.

git clone https://github.com/ggerganov/llama.cpp

Step 2: Move into the llama.cpp folder and build it with LLAMA_CURL=1 flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).

cd llama.cpp && LLAMA_CURL=1 make

Step 3: Run inference through the main binary.

./llama-cli --hf-repo Triangle104/Pantheon-RP-1.6.2-22b-Small-Q8_0-GGUF --hf-file pantheon-rp-1.6.2-22b-small-q8_0.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo Triangle104/Pantheon-RP-1.6.2-22b-Small-Q8_0-GGUF --hf-file pantheon-rp-1.6.2-22b-small-q8_0.gguf -c 2048