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--- |
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license: cc-by-nc-4.0 |
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tags: |
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- GGUF |
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- iMat |
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- llama3 |
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--- |
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``` |
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e88 88e d8 |
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d888 888b 8888 8888 ,"Y88b 888 8e d88 |
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C8888 8888D 8888 8888 "8" 888 888 88b d88888 |
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Y888 888P Y888 888P ,ee 888 888 888 888 |
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"88 88" "88 88" "88 888 888 888 888 |
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b |
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8b, |
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e88'Y88 d8 888 |
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d888 'Y ,"Y88b 888,8, d88 ,e e, 888 |
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C8888 "8" 888 888 " d88888 d88 88b 888 |
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Y888 ,d ,ee 888 888 888 888 , 888 |
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"88,d88 "88 888 888 888 "YeeP" 888 |
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PROUDLY PRESENTS |
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``` |
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## Llama-3-8B-EGO-iMat-GGUF |
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Quantized from fp32 with love. |
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* Weighted quantizations were calculated using groups_merged.txt with 105 chunks (recommended amount for this file) and n_ctx=512. Special thanks to jukofyork for sharing [this process](https://huggingface.co/jukofyork/WizardLM-2-8x22B-imatrix) |
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<b>**Note - Please use SillyTavern as well as the following prompt format:**</b> |
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``` |
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[EGO]Name: Character name and then Everything that forms the personality and speech patterns.(i.e. scenario, sample dialogue, character definitions, etc)[/EGO] |
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[SEEN]User message.[/SEEN] |
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Character Name: |
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``` |
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For a brief rundown of iMatrix quant performance please see this [PR](https://github.com/ggerganov/llama.cpp/pull/5747) |
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<b>All quants are verified working prior to uploading to repo for your safety and convenience. </b> |
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It's highly recommended to stick to higher quants of this model due to the unique nature of its pseudotokens |
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Original model card [here](https://huggingface.co/Envoid/Llama-3-8B-EGO) and below |
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--- |
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# This model isn't particularly great. It's just an undercooked experiment. |
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Releasing it anyways just in case it accidentally makes good merge meat. |
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# It also has a tendency to produce mature content without warning. |
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This model is tuned off of the base Llama-3-8B model. |
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I adapted the leaked Undi dataset into training samples for custom formatting. This model pretty much only functions properly in SillyTavern. |
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The formatting has two pairs of pseudotokens |
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``` |
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[EGO]Name: Character name and then Everything that forms the personality and speech patterns.(i.e. scenario, sample dialogue, character definitions, etc)[/EGO] |
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[SEEN]User message.[/SEEN] |
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Character Name: |
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``` |
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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. |
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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. |
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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. |
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It doesn't give particularly verbose replies unless you're continueing a roleplay with verbose messages. Otherwise it's pretty bad. |
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