athirdpath
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README.md
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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)
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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 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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