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--- |
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base_model: |
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- cognitivecomputations/dolphin-2.9.3-qwen2-1.5b |
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- Replete-AI/Qwen2-1.5b-Instruct-Replete-Adapted |
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- M4-ai/Hercules-5.0-Qwen2-1.5B |
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- d-llm/Qwen2-1.5B-Instruct-orpo |
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license: apache-2.0 |
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tags: |
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- moe |
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- frankenmoe |
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- merge |
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- mergekit |
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- lazymergekit |
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- cognitivecomputations/dolphin-2.9.3-qwen2-1.5b |
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- Replete-AI/Qwen2-1.5b-Instruct-Replete-Adapted |
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- M4-ai/Hercules-5.0-Qwen2-1.5B |
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- d-llm/Qwen2-1.5B-Instruct-orpo |
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--- |
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# Qwen2-4x1.5B-v2.5.1-A |
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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): |
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* [cognitivecomputations/dolphin-2.9.3-qwen2-1.5b](https://huggingface.co/cognitivecomputations/dolphin-2.9.3-qwen2-1.5b) |
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* [Replete-AI/Qwen2-1.5b-Instruct-Replete-Adapted](https://huggingface.co/Replete-AI/Qwen2-1.5b-Instruct-Replete-Adapted) |
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* [M4-ai/Hercules-5.0-Qwen2-1.5B](https://huggingface.co/M4-ai/Hercules-5.0-Qwen2-1.5B) |
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* [d-llm/Qwen2-1.5B-Instruct-orpo](https://huggingface.co/d-llm/Qwen2-1.5B-Instruct-orpo) |
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## 🧩 Configuration |
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```yaml |
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gate_mode: hidden |
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architecture: qwen |
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dtype: bfloat16 |
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experts_per_token: 2 |
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base_model: cognitivecomputations/dolphin-2.9.3-qwen2-1.5b |
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experts: |
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- source_model: cognitivecomputations/dolphin-2.9.3-qwen2-1.5b |
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positive_prompts: |
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- "You are an educator, provide in-depth explanations on academic topics." |
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- "You are a tutor, offer guidance and support on complex subjects." |
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negative_prompts: |
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- "code" |
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- "algorithm" |
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- "programming" |
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- source_model: Replete-AI/Qwen2-1.5b-Instruct-Replete-Adapted |
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positive_prompts: |
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- "You are a software developer, write code in various programming languages to solve complex problems." |
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- "You are a programmer, design and implement algorithms to optimize system performance." |
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negative_prompts: |
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- "explain" |
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- "describe" |
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- "define" |
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- source_model: M4-ai/Hercules-5.0-Qwen2-1.5B |
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positive_prompts: |
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- "You are a content creator, rephrase and reorganize text to improve clarity and coherence." |
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- "You are a writer, generate engaging and informative content on a wide range of topics." |
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- "You are a knowledge expert, provide general knowledge on history, science, literature, and more." |
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negative_prompts: |
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- "code" |
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- "algorithm" |
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- "programming" |
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- source_model: d-llm/Qwen2-1.5B-Instruct-orpo |
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positive_prompts: |
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- "You are a summarizer, condense complex information into concise summaries." |
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- "You are a translator, translate text from one language to another while preserving meaning and context." |
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negative_prompts: |
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- "explain" |
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- "describe" |
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- "define" |
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shared_experts: |
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- source_model: cognitivecomputations/dolphin-2.9.3-qwen2-1.5b |
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positive_prompts: |
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- "You are a conversationalist, engage in natural-sounding conversations on a wide range of topics." |
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negative_prompts: |
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- "code" |
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- "algorithm" |
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- "programming" |
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residual_scale: 0.1 |
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``` |
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## 💻 Usage |
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```python |
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!pip install -qU transformers bitsandbytes accelerate |
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from transformers import AutoTokenizer, pipeline |
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import torch |
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model = "djuna/Qwen2-4x1.5B-v2.5.1-A" |
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tokenizer = AutoTokenizer.from_pretrained(model) |
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generator = pipeline( |
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"text-generation", |
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model=model, |
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model_kwargs={"torch_dtype": torch.float16, "load_in_4bit": True}, |
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) |
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messages = [{"role": "user", "content": "Explain what a Mixture of Experts is in less than 100 words."}] |
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prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True) |
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outputs = generator(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95) |
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print(outputs[0]["generated_text"]) |
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``` |
