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  # Limamono-7B (Mistral) v0.3
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  This is a very early version of a strongly NSFW roleplaying model with _extremely limited amounts_
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- of almost entirely synthetic data of hopefully higher quality than typical human conversations.
 
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  Limamono tries to address the main issues and limitations of the previously released [LimaRP](https://huggingface.co/datasets/lemonilia/LimaRP)
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  and is composed of extensively modified conversations written with the help of base [Yi-34](https://huggingface.co/01-ai/Yi-34B)
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  **Note**: there is currently no plan to release the dataset.
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  ## Prompt format
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  Limamono uses the [extended Alpaca format](https://github.com/tatsu-lab/stanford_alpaca),
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  with `### Input:` immediately preceding user inputs and `### Response:` immediately preceding
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  This has an effect on bot responses, but as of now it might not always reliably work. The lengths
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  using during training are: `micro`, `tiny`, `short`, `medium`, `long`, `massive`, `huge`.
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- - It is recommended not to use a length modifier at all for character responses, except as a
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- _temporary measure_ for increasing message length.
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- - It is suggested to add `(length = tiny)` to the `### Input:` sequence, on the other hand.
 
 
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  ## Prose style
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  Only The Novel/Forum RP style is supported.
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  - `''The Jungle Book''`
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  - Punctuation has been normalized and tries to follow standard convensions for book/novel writing.
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  ## Example
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  This is how a typical RP chat may take place with this model. Note the presence of
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  character thoughts.
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  ![example](https://files.catbox.moe/ch2bo2.png)
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  ## Training procedure
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  [Axolotl](https://github.com/OpenAccess-AI-Collective/axolotl) was used for training
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  on one NVidia RTX3090.
 
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  # Limamono-7B (Mistral) v0.3
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  This is a very early version of a strongly NSFW roleplaying model with _extremely limited amounts_
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+ of almost entirely synthetic data of hopefully higher quality than typical human conversations. The
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+ intended model audience is straight men and lesbians.
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  Limamono tries to address the main issues and limitations of the previously released [LimaRP](https://huggingface.co/datasets/lemonilia/LimaRP)
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  and is composed of extensively modified conversations written with the help of base [Yi-34](https://huggingface.co/01-ai/Yi-34B)
 
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  **Note**: there is currently no plan to release the dataset.
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+ ## Known issues and quirks
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+ - The model may feel somewhat "overbaked".
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+ - Impersonation may still sometimes occur early in the chat, in particular when trying to force a long
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+ character message length.
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+
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  ## Prompt format
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  Limamono uses the [extended Alpaca format](https://github.com/tatsu-lab/stanford_alpaca),
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  with `### Input:` immediately preceding user inputs and `### Response:` immediately preceding
 
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  This has an effect on bot responses, but as of now it might not always reliably work. The lengths
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  using during training are: `micro`, `tiny`, `short`, `medium`, `long`, `massive`, `huge`.
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+ However, it is recommended **not** to use a length modifier at all for character responses, except as a
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+ _temporary measure_ for increasing message length in case they become too short.
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+
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+ On the other hand, it is suggested to add `(length = tiny)` or `(length = short)` to the
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+ `### Input:` sequence, in order to help the model follow more closely its training data.
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  ## Prose style
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  Only The Novel/Forum RP style is supported.
 
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  - `''The Jungle Book''`
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  - Punctuation has been normalized and tries to follow standard convensions for book/novel writing.
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+ ## SillyTavern settings
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+ Try to follow these settings. Appropriate files for replicating them are included in the model
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+ repository:
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+
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+ ![ST settings](https://files.catbox.moe/z9q0g2.png)
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+
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  ## Example
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  This is how a typical RP chat may take place with this model. Note the presence of
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  character thoughts.
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  ![example](https://files.catbox.moe/ch2bo2.png)
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+ You can try chatting with Charlotte by downloading her [SillyTavern character card](https://huggingface.co/lemonilia/Limamono-Mistral-7B-v0.3/blob/main/Charlotte.png)
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+ in the repository.
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+
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  ## Training procedure
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  [Axolotl](https://github.com/OpenAccess-AI-Collective/axolotl) was used for training
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  on one NVidia RTX3090.