DeepQwenScalerPlus

DeepQwenScalerPlus is a merge of the following models using LazyMergekit:

• Qwen/Qwen2.5-Coder-1.5B-Instruct
• Qwen/Qwen2.5-Math-1.5B-Instruct
• Qwen/Qwen2.5-1.5B
• agentica-org/DeepScaleR-1.5B-Preview

🧩 Configuration

models:
  - model: deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
    # no parameters necessary for base model
  - model: Qwen/Qwen2.5-Coder-1.5B-Instruct
    parameters:
      density: 0.5
      weight: 0.5
  - model: Qwen/Qwen2.5-Math-1.5B-Instruct
    parameters:
      density: 0.6
      weight: 0.5
  - model: Qwen/Qwen2.5-1.5B
    parameters:
      density: 0.6
      weight: 0.5
  - model: agentica-org/DeepScaleR-1.5B-Preview
    parameters:
      density: 0.4
      weight: 0.6
merge_method: ties
base_model: deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
parameters:
  normalize: true
dtype: float16

💻 Usage

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "K00B404/DeepQwenScalerPlus"
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"])