---
base_model:
- cognitivecomputations/dolphin-2.9.3-qwen2-1.5b
- Replete-AI/Qwen2-1.5b-Instruct-Replete-Adapted
- M4-ai/Hercules-5.0-Qwen2-1.5B
- d-llm/Qwen2-1.5B-Instruct-orpo
license: apache-2.0
tags:
- moe
- frankenmoe
- merge
- mergekit
- lazymergekit
- cognitivecomputations/dolphin-2.9.3-qwen2-1.5b
- Replete-AI/Qwen2-1.5b-Instruct-Replete-Adapted
- M4-ai/Hercules-5.0-Qwen2-1.5B
- d-llm/Qwen2-1.5B-Instruct-orpo
---

# Qwen2-4x1.5B-v2.5.1-A

Qwen2-4x1.5B-v2.5.1-A is a Mixture of Experts (MoE) made with the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [cognitivecomputations/dolphin-2.9.3-qwen2-1.5b](https://huggingface.co/cognitivecomputations/dolphin-2.9.3-qwen2-1.5b)
* [Replete-AI/Qwen2-1.5b-Instruct-Replete-Adapted](https://huggingface.co/Replete-AI/Qwen2-1.5b-Instruct-Replete-Adapted)
* [M4-ai/Hercules-5.0-Qwen2-1.5B](https://huggingface.co/M4-ai/Hercules-5.0-Qwen2-1.5B)
* [d-llm/Qwen2-1.5B-Instruct-orpo](https://huggingface.co/d-llm/Qwen2-1.5B-Instruct-orpo)


## 🧩 Configuration

```yaml
gate_mode: hidden
architecture: qwen
dtype: bfloat16
experts_per_token: 2
base_model: cognitivecomputations/dolphin-2.9.3-qwen2-1.5b
experts:
  - source_model: cognitivecomputations/dolphin-2.9.3-qwen2-1.5b
    positive_prompts:
      - "You are an educator, provide in-depth explanations on academic topics."
      - "You are a tutor, offer guidance and support on complex subjects."
    negative_prompts:
      - "code"
      - "algorithm"
      - "programming"
  - source_model: Replete-AI/Qwen2-1.5b-Instruct-Replete-Adapted
    positive_prompts:
      - "You are a software developer, write code in various programming languages to solve complex problems."
      - "You are a programmer, design and implement algorithms to optimize system performance."
    negative_prompts:
      - "explain"
      - "describe"
      - "define"
  - source_model: M4-ai/Hercules-5.0-Qwen2-1.5B
    positive_prompts:
      - "You are a content creator, rephrase and reorganize text to improve clarity and coherence."
      - "You are a writer, generate engaging and informative content on a wide range of topics."
      - "You are a knowledge expert, provide general knowledge on history, science, literature, and more."
    negative_prompts:
      - "code"
      - "algorithm"
      - "programming"
  - source_model: d-llm/Qwen2-1.5B-Instruct-orpo
    positive_prompts:
      - "You are a summarizer, condense complex information into concise summaries."
      - "You are a translator, translate text from one language to another while preserving meaning and context."
    negative_prompts:
      - "explain"
      - "describe"
      - "define"
shared_experts:
  - source_model: cognitivecomputations/dolphin-2.9.3-qwen2-1.5b
    positive_prompts:
      - "You are a conversationalist, engage in natural-sounding conversations on a wide range of topics."
    negative_prompts:
      - "code"
      - "algorithm"
      - "programming"
    residual_scale: 0.1


```

## 💻 Usage

```python
!pip install -qU transformers bitsandbytes accelerate

from transformers import AutoTokenizer, pipeline
import torch

model = "djuna/Qwen2-4x1.5B-v2.5.1-A"

tokenizer = AutoTokenizer.from_pretrained(model)
generator = pipeline(
    "text-generation",
    model=model,
    model_kwargs={"torch_dtype": torch.float16, "load_in_4bit": True},
)

messages = [{"role": "user", "content": "Explain what a Mixture of Experts is in less than 100 words."}]
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
outputs = generator(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
```