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- config.json +30 -0
- mergekit_config.yml +10 -0
- model-00001-of-00014.safetensors +3 -0
- model-00002-of-00014.safetensors +3 -0
- model-00003-of-00014.safetensors +3 -0
- model-00004-of-00014.safetensors +3 -0
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- model-00010-of-00014.safetensors +3 -0
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- model-00013-of-00014.safetensors +3 -0
- model-00014-of-00014.safetensors +3 -0
- model.safetensors.index.json +1 -0
- special_tokens_map.json +30 -0
- tokenizer.json +0 -0
- tokenizer.model +3 -0
- tokenizer_config.json +43 -0
README.md
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---
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tags:
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- merge
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- mergekit
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- lazymergekit
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- KoboldAI/LLaMA2-13B-Tiefighter
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- DavidAU/D_AU-Tiefighter-OrcaMaid-V3-13B-32k-slerp
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base_model:
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- KoboldAI/LLaMA2-13B-Tiefighter
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- DavidAU/D_AU-Tiefighter-OrcaMaid-V3-13B-32k-slerp
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---
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# D_AU-Tiefighter-Plus-OrcaMaid-V3-13B-32k-slerp
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D_AU-Tiefighter-Plus-OrcaMaid-V3-13B-32k-slerp is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
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* [KoboldAI/LLaMA2-13B-Tiefighter](https://huggingface.co/KoboldAI/LLaMA2-13B-Tiefighter)
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* [DavidAU/D_AU-Tiefighter-OrcaMaid-V3-13B-32k-slerp](https://huggingface.co/DavidAU/D_AU-Tiefighter-OrcaMaid-V3-13B-32k-slerp)
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## 🧩 Configuration
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```yaml
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models:
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- model: KoboldAI/LLaMA2-13B-Tiefighter
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parameters:
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weight: 0.6
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- model: DavidAU/D_AU-Tiefighter-OrcaMaid-V3-13B-32k-slerp
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parameters:
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weight: 0.4
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merge_method: linear
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dtype: bfloat16
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```
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## 💻 Usage
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```python
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!pip install -qU transformers accelerate
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from transformers import AutoTokenizer
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import transformers
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import torch
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model = "DavidAU/D_AU-Tiefighter-Plus-OrcaMaid-V3-13B-32k-slerp"
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messages = [{"role": "user", "content": "What is a large language model?"}]
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tokenizer = AutoTokenizer.from_pretrained(model)
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prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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pipeline = transformers.pipeline(
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"text-generation",
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model=model,
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torch_dtype=torch.float16,
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device_map="auto",
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)
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outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
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print(outputs[0]["generated_text"])
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```
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config.json
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{
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"_name_or_path": "KoboldAI/LLaMA2-13B-Tiefighter",
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"architectures": [
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"LlamaForCausalLM"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"bos_token_id": 1,
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"eos_token_id": 2,
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"hidden_act": "silu",
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"hidden_size": 5120,
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"initializer_range": 0.02,
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"intermediate_size": 13824,
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"max_position_embeddings": 4096,
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"model_type": "llama",
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"num_attention_heads": 40,
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"num_hidden_layers": 40,
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"num_key_value_heads": 40,
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"pad_token_id": 0,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-05,
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"rope_scaling": null,
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"rope_theta": 10000.0,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.40.1",
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"use_cache": true,
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"vocab_size": 32000,
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"welcome": "# Welcome to Tiefighter by KoboldAI Henky!! \nTiefighter is a unique merge model that combines the best of fictional use cases into one model, a true all-rounder.\nThis does mean that the model may take some steering in the beginning of your session to guide it towards what you want to do.\n\nThis model is meant to be creative, If you let it improvise you get better results than if you drown it in details.\n\n## Story Writing\nRegular 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.\n\n### Generate a story on demand\nTo 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.\n\n## Chatbots and persona's\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 Henk where they discuss language models.\nIn this conversation Henk is excited to teach Alice about Tiefigther. \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.\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 awesome work from: \nUndi95, 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."
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}
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mergekit_config.yml
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models:
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- model: KoboldAI/LLaMA2-13B-Tiefighter
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parameters:
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weight: 0.6
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- model: DavidAU/D_AU-Tiefighter-OrcaMaid-V3-13B-32k-slerp
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parameters:
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weight: 0.4
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merge_method: linear
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dtype: bfloat16
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special_tokens_map.json
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tokenizer.json
ADDED
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tokenizer.model
ADDED
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tokenizer_config.json
ADDED
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