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Unhinged and Happy:

Second experiment in building an unpredicatable model based on TWO creative based LLMs.

After blowing up LazyMergekit in Colab 3 times... here we are.

This merge takes "Layer Theory", "Merge Rules" and throws some of it out the window.

Bottom line if you want an unhinged creative journey... start here.

This merged model is uncensored, freak of nature creative and slightly crazy.

It will break from time to time, and it will not likely win any LLM "testing" awards.

But when it works... oh boy.

It will follow your instructions (mostly) but I suggest lowering temp a bit if it starts going off the rails.

If you are looking for a model for Roleplay, Creative writing, or Entertainment value this is it.

Keep in mind the prose can be slightly "off" at times, which seems to be a by-product of this type of merge.

Tuned (a bit de-hinged?) to be built and tested later.

Context Length: 4096

Please see orginal model cards (Tiefighter and Holomax) for more details below.

D_AU-Tiefighter-Holomax-15B-UNHINGED-V1

D_AU-Tiefighter-Holomax-15B-UNHINGED-V1 is a merge of the following models using LazyMergekit:

🧩 Configuration

slices:
  - sources:
    - model: KoboldAI/LLaMA2-13B-Tiefighter
      layer_range: [0, 10]
  - sources:
    - model: KoboldAI/LLaMA2-13B-Holomax
      layer_range: [11,15]
  - sources:
    - model: KoboldAI/LLaMA2-13B-Tiefighter
      layer_range: [16,20]
  - sources:
    - model: KoboldAI/LLaMA2-13B-Holomax
      layer_range: [16,22]
  - sources:
    - model: KoboldAI/LLaMA2-13B-Tiefighter
      layer_range: [21, 30]
  - sources:
    - model: KoboldAI/LLaMA2-13B-Holomax
      layer_range: [31,33]
  - sources:
    - model: KoboldAI/LLaMA2-13B-Tiefighter
      layer_range: [31,35]
  - sources:
    - model: KoboldAI/LLaMA2-13B-Holomax
      layer_range: [36,40]
  - sources:
    - model: KoboldAI/LLaMA2-13B-Tiefighter
      layer_range: [36,40]
merge_method: passthrough
dtype: bfloat16

πŸ’» Usage

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "DavidAU/D_AU-Tiefighter-Holomax-20B-V1"
messages = [{"role": "user", "content": "What is a large language model?"}]

tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
    "text-generation",
    model=model,
    torch_dtype=torch.float16,
    device_map="auto",
)

outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
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