tomasmcm / llama2-13b-tiefighter

Source: KoboldAI/LLaMA2-13B-Tiefighter ✦ Quant: TheBloke/LLaMA2-13B-Tiefighter-AWQ ✦ A merged model achieved trough merging two different lora's on top of a well established existing merge

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Run time and cost

This model runs on Nvidia A40 GPU hardware. Predictions typically complete within 3 seconds.



Tiefighter is a merged model achieved trough merging two different lora’s on top of a well established existing merge. To achieve this the following recipe was used:

  • We begin with the base model Undi95/Xwin-MLewd-13B-V0.2 which is a well established merged, contrary to the name this model does not have a strong NSFW bias.
  • Then we applied the PocketDoc/Dans-RetroRodeo-13b lora which is a finetune on the Choose your own Adventure datasets from our Skein model.
  • After applying this lora we merged the new model with PocketDoc/Dans-RetroRodeo-13b at 5% to weaken the newly introduced adventure bias.
  • The resulting merge was used as a new basemodel to which we applied Blackroot/Llama-2-13B-Storywriter-LORA and repeated the same trick, this time at 10%.

This means this model contains the following ingredients from their upstream models for as far as we can track them:

  • Undi95/Xwin-MLewd-13B-V0.2
    • Undi95/ReMM-S-Light
  • Undi95/CreativeEngine
  • Brouz/Slerpeno
    • elinas/chronos-13b-v2
    • jondurbin/airoboros-l2-13b-2.1
    • NousResearch/Nous-Hermes-Llama2-13b+nRuaif/Kimiko-v2
    • CalderaAI/13B-Legerdemain-L2+lemonilia/limarp-llama2-v2
      • KoboldAI/LLAMA2-13B-Holodeck-1
    • NousResearch/Nous-Hermes-13b
    • OpenAssistant/llama2-13b-orca-8k-3319
    • ehartford/WizardLM-1.0-Uncensored-Llama2-13b
    • Henk717/spring-dragon
  • The-Face-Of-Goonery/Huginn-v3-13b (Contains undisclosed model versions, those we assumed where possible)
    • SuperCOT (Undisclosed version)
    • elinas/chronos-13b-v2 (Version assumed)
    • NousResearch/Nous-Hermes-Llama2-13b
    • stabilityai/StableBeluga-13B (Version assumed)
  • zattio770/120-Days-of-LORA-v2-13B
  • PygmalionAI/pygmalion-2-13b
  • Undi95/Storytelling-v1-13B-lora
  • TokenBender/sakhi_13B_roleplayer_NSFW_chat_adapter
  • nRuaif/Kimiko-v2-13B
  • The-Face-Of-Goonery/Huginn-13b-FP16
    • “a lot of different models, like hermes, beluga, airoboros, chronos.. limarp”
  • lemonilia/LimaRP-Llama2-13B-v3-EXPERIMENT
  • Xwin-LM/Xwin-LM-13B-V0.2
  • PocketDoc/Dans-RetroRodeo-13b
  • Blackroot/Llama-2-13B-Storywriter-LORA

While we could possibly not credit every single lora or model involved in this merged model, we’d like to thank all involved creators upstream for making this awesome model possible! Thanks to you the AI ecosystem is thriving, and without your dedicated tuning efforts models such as this one would not be possible.


This model is meant to be creative, If you let it improvise you get better results than if you drown it in details.

Story Writing

Regular story writing in the traditional way is supported, simply copy paste your story and continue writing. Optionally use an instruction in memory or an authors note to guide the direction of your story.

Generate a story on demand

To generate stories on demand you can use an instruction (tested in the Alpaca format) such as “Write a novel about X, use chapters and dialogue” this will generate a story. The format can vary between generations depending on how the model chooses to begin, either write what you want as shown in the earlier example or write the beginning of the story yourself so the model can follow your style. A few retries can also help if the model gets it wrong.

Chatbots and persona’s

This model has been tested with various forms of chatting, testers have found that typically less is more and the model is good at improvising. Don’t drown the model in paragraphs of detailed information, instead keep it simple first and see how far you can lean on the models own ability to figure out your character. Copy pasting paragraphs of background information is not suitable for a 13B model such as this one, code formatted characters or an instruction prompt describing who you wish to talk to goes much further.

For example, you can put this in memory in regular chat mode:

### Instruction: 
Generate a conversation between Alice and Henk where they discuss language models.
In this conversation Henk is excited to teach Alice about Tiefigther. 
### Response: 

Because the model is a merge of a variety of models, it should support a broad range of instruct formats, or plain chat mode. If you have a particular favourite try it, otherwise we recommend to either use the regular chat mode or Alpaca’s format.

Instruct Prompting

This model features various instruct models on a variety of instruction styles, when testing the model we have used Alpaca for our own tests. If you prefer a different format chances are it can work.

During instructions we have observed that in some cases the adventure data can leak, it may also be worth experimenting using > as the prefix for a user command to remedy this. But this may result in a stronger fiction bias.

Keep in mind that while this model can be used as a factual instruct model, the focus was on fiction. Information provided by the model can be made up.

Adventuring and Adventure Games

This model contains a lora that was trained on the same adventure dataset as the KoboldAI Skein model. Adventuring is best done using an small introduction to the world and your objective while using the > prefix for a user command (KoboldAI’s adventure mode).

It is possible that the model does not immediately pick up on what you wish to do and does not engage in its Adventure mode behaviour right away. Simply manually correct the output to trim excess dialogue or other undesirable behaviour and continue to submit your actions using the appropriate mode. The model should pick up on this style quickly and will correctly follow this format within 3 turns.

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