Note: The merge method is ties, not slerp.

Neural-Cosmic-Boy-7B-slerp

Neural-Cosmic-Boy-7B-slerp is a merge of the following models using LazyMergekit:

• Kukedlc/Neural-Cosmic-7B-slerp
• Kukedlc/NeuralLogic-7B-V
• Kukedlc/SuperCombo

🧩 Configuration

models:
  - model: Kukedlc/Neural-Cosmic-7B-slerp
    parameters:
      density: [1, 0.7, 0.1] # density gradient
      weight: 1.0
  - model: Kukedlc/NeuralLogic-7B-V
    parameters:
      density: 0.5
      weight: [0, 0.3, 0.7, 1] # weight gradient
  - model: Kukedlc/SuperCombo
    parameters:
      density: 0.33
      weight:
        - filter: mlp
          value: 0.5
        - value: 0
merge_method: ties
base_model: mistralai/Mistral-7B-v0.1
parameters:
  normalize: true
  int8_mask: true
dtype: float16

💻 Usage

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "Kukedlc/Neural-Cosmic-Boy-7B-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"])

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric	Value
Avg.	74.08
AI2 Reasoning Challenge (25-Shot)	70.48
HellaSwag (10-Shot)	87.65
MMLU (5-Shot)	64.92
TruthfulQA (0-shot)	67.10
Winogrande (5-shot)	82.00
GSM8k (5-shot)	72.33