metadata

tags:
  - merge
  - mergekit
  - lazymergekit
  - KoboldAI/LLaMA2-13B-Tiefighter
  - KoboldAI/LLaMA2-13B-Holomax
base_model:
  - KoboldAI/LLaMA2-13B-Tiefighter
  - KoboldAI/LLaMA2-13B-Holomax
  - KoboldAI/LLaMA2-13B-Tiefighter
  - KoboldAI/LLaMA2-13B-Holomax
  - KoboldAI/LLaMA2-13B-Tiefighter
  - KoboldAI/LLaMA2-13B-Holomax
  - KoboldAI/LLaMA2-13B-Tiefighter
  - KoboldAI/LLaMA2-13B-Holomax
  - KoboldAI/LLaMA2-13B-Tiefighter

D_AU-Tiefighter-Holomax-20B-V1

D_AU-Tiefighter-Holomax-20B-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

💻 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"])