DeepCode-7B-Aurora-v4

DeepCode-7B-Aurora-v4

DeepCode-7B-Aurora-v4 is a merge of the following models using LazyMergekit:

• Kukedlc/NeuralMaths-Experiment-7b
• lemon-mint/gemma-ko-7b-instruct-v0.62
• Ppoyaa/StarMonarch-7B
• automerger/YamshadowExperiment28-7B
• ichigoberry/MonarchPipe-7B-slerp
• deepseek-ai/deepseek-coder-7b-instruct-v1.5
• Kukedlc/Neural-4-Maths-7b

🧩 Configuration

models:
  - model: Kukedlc/NeuralMaths-Experiment-7b
    parameters:
      weight: 1
  - model: lemon-mint/gemma-ko-7b-instruct-v0.62
    parameters:
      weight: 1
  - model: Ppoyaa/StarMonarch-7B
    parameters:
      weight: 1
  - model: automerger/YamshadowExperiment28-7B
    parameters:
      weight: 1
  - model: ichigoberry/MonarchPipe-7B-slerp
    parameters:
      weight: 1
  - model: deepseek-ai/deepseek-coder-7b-instruct-v1.5
    parameters:
      weight: 1
  - model: Kukedlc/Neural-4-Maths-7b
    parameters:
      weight: 1
merge_method: task_arithmetic
base_model: deepseek-ai/deepseek-math-7b-rl
parameters:
  normalize: true
  int8_mask: true
dtype: float16

💻 Usage

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "ALBADDAWI/DeepCode-7B-Aurora-v4"
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"])