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@@ -19,11 +19,18 @@ It achieves the following results on the evaluation set:
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  ## Model description
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- athirdpath/Nethena-20b-Glued-LORA is a 128 rank LORA for RP, trained on [NeverSleep/Nethena-20B](https://huggingface.co/NeverSleep/Nethena-20B) with a private dataset. It is unalligned and NSFW-oriented.
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  This is a test, exploring the effects of "gluing" the components of the 20b model together to reduce the iconic word replacement errors, increase lucidity, and improve recall.
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- So far it is passing subjective testing with flying colors, objective numbers coming soon.
 
 
 
 
 
 
 
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  ### Training hyperparameters
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  ## Model description
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+ athirdpath/Nethena-20b-Glued-LORA is a 128 rank LORA for RP, trained on [NeverSleep/Nethena-20B](https://huggingface.co/NeverSleep/Nethena-20B). It is unalligned and NSFW-oriented.
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  This is a test, exploring the effects of "gluing" the components of the 20b model together to reduce the iconic word replacement errors, increase lucidity, and improve recall.
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+ ## Training and evaluation data
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+ The private ~500k token dataset used to train the LORA was Alpaca formatted and focused on 4 primary categories:
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+ - Medical texts (on psychology, reproductive organs, anatomy, and pregnancy). These are formatted so the model, in character as a doctor or therapist, answers a patient's question in short to medium form.
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+ - Excerpts from short stories and novellas (erotic and romantic) centered around both realistic and fantastic situations, covering several fetishes as well. These are sliced into ~2048 token chunks, and these long-form responses are all tied to the command “Enter narrator mode.” in the instructions.
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+ - A selection from PIPPA, using a wide keyword search for tokens associated with low quality human or AI data to remove those responses, then a positive search was done for words and phrases associated with a higher reading level. These are converted to Alpaca with “Enter RP mode.” in all the instruction fields.
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+ - ~18k tokens of GPT-4 generated data on role-playing from various characters’ perspectives, focusing on different situations and emotions. Includes many multi-turn conversations.
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  ### Training hyperparameters
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