config.json

{
  "_name_or_path": "KoboldAI/LLaMA2-13B-Psyfighter2",
  "architectures": [
    "LlamaForCausalLM"
  ],
  "attention_bias": false,
  "attention_dropout": 0.0,
  "bos_token_id": 1,
  "eos_token_id": 2,
  "hidden_act": "silu",
  "hidden_size": 5120,
  "initializer_range": 0.02,
  "intermediate_size": 13824,
  "max_position_embeddings": 4096,
  "mlp_bias": false,
  "model_type": "llama",
  "num_attention_heads": 40,
  "num_hidden_layers": 32,
  "num_key_value_heads": 40,
  "pad_token_id": 0,
  "pretraining_tp": 1,
  "rms_norm_eps": 1e-05,
  "rope_scaling": null,
  "rope_theta": 10000.0,
  "tie_word_embeddings": false,
  "torch_dtype": "bfloat16",
  "transformers_version": "4.41.0",
  "use_cache": true,
  "vocab_size": 32000,
  "welcome": "# Welcome to Psyfighter2 by Jeb Carter and Twistedshadows \nPsyfighter2 is a creative writing focused model built on Henk717's Tiefighter. The addition of medical and psychological data to the model directs its attention toward psychological and spatial details, which improves the writing output by encouraging the model to focus on more relevant details.\n\nThe key to working with PsyfighterV2 is to the understand that Less Is More.\nThis model is meant to be creative, If you let it improvise you will get better results than if you drown it in details, which can scatter and shatter the model's focus. If your back end supports it, we recommend setting a min-p of 0.05. \n\n## Story Writing\nStory co-writing is supported in the traditional way - simply start your story and invoke the model's completions as needed. To guide the model at a higher level we recommend using this format to generate stories on demand or help shape the outputs the model will use in its story continuations.\n\n\n``` \nURL: https://www.gutenberg.org/$AuthorName/Stories \n\nTitle:\nTags:\nSynopsis:\nNotes:\nFirst Publication: $MagazineName, $YEAR\n\n$Title\n\nA $Genre [Tale|Story|Novel]\n\nby $AuthorName\n```\nnThe author name has the heaviest influence on the writing style, but you can shape the output through tags, setting a year of imaginary first publication, and proving commentary in Notes can tell the model how the story is expected to go.## Chatbots and personas\nThis 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.\n\nFor example, you can put this in memory in regular chat mode:\n``` \n### Instruction: \nGenerate a conversation between Alice and Jeb where they discuss language models.\nIn this conversation Jeb is excited to teach Alice about Psyfighter. \n### Response: \n```\n\nBecause 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.\n\n## Instruct Prompting\nThis 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.\n\nDuring 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. If using Instruct style directions during chat or storywriting, you can enclose your direction in formatting like this to keep it from contaminating the rest of the context: \n```\n***\n> [Instructions/Direction here]\n***\n```\n\nKeep 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.\n\n## Adventuring and Adventure Games\nThis 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). \n\nIt 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.\n\n## Discovered something cool and want to engage with us? \nJoin our community at https://koboldai.org/discord !\n\n### This model would not be possible without the KoboldAI MergeBox program and the awesome work from: \nDoctor Shotgun, Undi95, PocketDoc, Blackroot, Brouz, The Face of Goonery, zattio770, PygmalionAI, TokenBender, nRuaif, lemonilia, Xwin-LM, elinas, jondurbin, NousResearch, CalderaAI, MrSeeker, OpenAssistant, ehartford, Henk717, AI Dungeon, StabilityAI and zattio770."
}