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PROUDLY PRESENTS

Llama-3-8B-Instruct-DADA-exl2-rpcal

Quantized using 200 samples of 8192 tokens from an RP-oriented PIPPA dataset.

Branches:

main -- measurement.json
8b8h -- 8bpw, 8bit lm_head
6b6h -- 6bpw, 6bit lm_head
4b6h -- 4bpw, 6bit lm_head

Original model link: Envoid/Llama-3-8B-EGO

Original model README below.

This model isn't particularly great. It's just an undercooked experiment.

Releasing it anyways just in case it accidentally makes good merge meat.

It also has a tendency to produce mature content without warning.

This model is tuned off of the base Llama-3-8B model.

I adapted the leaked Undi dataset into training samples for custom formatting. This model pretty much only functions properly in SillyTavern.

The formatting has two pairs of pseudotokens

[EGO]Name: Character name and then Everything that forms the personality and speech patterns.(i.e. scenario, sample dialogue, character definitions, etc)[/EGO]
[SEEN]User message.[/SEEN]
Character Name:

The self attention modules were fine tuned separately on this dataset and the pseudotokens were chosen because they made logical sense with respect to the character giving a reply without allowing the model to 'connect the dots' during training and figure out that it is indeed an AI language model.

After this was done all modules were then finetuned together on the dendrite dataset in order to connect the changes made to the attention modules.

So with regards to building a SillyTavern prompt template you basically want the entire story string and any additional stylistic instructions enclosed in the [EGO] tags and then the user messages enclosed in [SEEN] tags.

It doesn't give particularly verbose replies unless you're continueing a roleplay with verbose messages. Otherwise it's pretty bad.

GGUFs care of Qaunt Cartel