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README.md
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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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- Characters may occasionally exhibit strange (unintended) speech quirks. Please report if found.
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- Impersonation may sometimes occur early in the chat, in particular when trying to force a very
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long character message length or regenerating the greeting message.
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should be placed with a space _after_ the colon:
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```
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### Response: (length =
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{{char}}: [utterance]
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### Input: (length = tiny)
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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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used during training are: `micro`, `tiny`, `short`, `medium`, `long`, `massive`, `huge`.
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From extended testing, a **long** length was found to work reasonably well.
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It is also 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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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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## 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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**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". Use a temperature of 1.
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- Characters may occasionally exhibit strange (unintended) speech quirks. Please report if found.
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- Impersonation may sometimes occur early in the chat, in particular when trying to force a very
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long character message length or regenerating the greeting message.
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should be placed with a space _after_ the colon:
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```
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### Response: (length = long)
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{{char}}: [utterance]
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### Input: (length = tiny)
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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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used during training are: `micro`, `tiny`, `short`, `medium`, `long`, `massive`, `huge`.
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From extended testing, a **long** length was found to work reasonably well. In the training data,
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bot messages are usually `long`, `massive` and `huge`, with the largest size generally only for
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the greeting messages.
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It is also 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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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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## Text generation settings
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For testing I use these settings:
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- Temperature: 1.0
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- Tail-Free Sampling: 0.85–0.89
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- Repetition Penalty: 1.11
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- Repetition Penalty range: 2048
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- Top-p: 1 (disabled), Top-k: 0 (disabled)
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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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