README.md

metadata

tags:
  - merge
  - mergekit
  - lazymergekit
  - KoboldAI/LLaMA2-13B-Tiefighter
  - DavidAU/D_AU-Tiefighter-Giraffe-13B-32k-slerp
base_model:
  - KoboldAI/LLaMA2-13B-Tiefighter
  - DavidAU/D_AU-Tiefighter-Giraffe-13B-32k-slerp

Version 2:

Attempt to use linear "retraining" to fix issues with orginal model (D_AU-Tiefighter-Giraffe-13B-32k-slerp) merge from step 1.

Seems to be successful.

Model is working correctly and GGUFs are also working correctly with context at 32768.

Imatrix Plus GGUFs upload to follow shortly.

D_AU-Tiefighter-Plus-Giraffe-13B-32k-slerp

D_AU-Tiefighter-Plus-Giraffe-13B-32k-slerp is a merge of the following models using LazyMergekit:

• KoboldAI/LLaMA2-13B-Tiefighter
• DavidAU/D_AU-Tiefighter-Giraffe-13B-32k-slerp

🧩 Configuration

models:
  - model: KoboldAI/LLaMA2-13B-Tiefighter
    parameters:
      weight: 0.8
  - model: DavidAU/D_AU-Tiefighter-Giraffe-13B-32k-slerp
    parameters:
      weight: 0.2
merge_method: linear
dtype: bfloat16

💻 Usage

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "DavidAU/D_AU-Tiefighter-Plus-Giraffe-13B-32k-slerp"
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"])