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--- |
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license: apache-2.0 |
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tags: |
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- moe |
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- merge |
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- mergekit |
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- lazymergekit |
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- Qwen/Qwen1.5-0.5B |
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--- |
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# TinyQwex-4x620M-MoE |
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TinyQwex-4x620M-MoE is a Mixure of Experts (MoE) made with the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing): |
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* [Qwen/Qwen1.5-0.5B](https://huggingface.co/Qwen/Qwen1.5-0.5B) |
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* [Qwen/Qwen1.5-0.5B](https://huggingface.co/Qwen/Qwen1.5-0.5B) |
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* [Qwen/Qwen1.5-0.5B](https://huggingface.co/Qwen/Qwen1.5-0.5B) |
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* [Qwen/Qwen1.5-0.5B](https://huggingface.co/Qwen/Qwen1.5-0.5B) |
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## 🧩 Configuration |
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```yamlbase_model: Qwen/Qwen1.5-0.5B |
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experts: |
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- source_model: Qwen/Qwen1.5-0.5B |
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positive_prompts: |
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- "reasoning" |
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- "logic" |
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- "problem-solving" |
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- "critical thinking" |
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- "analysis" |
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- "synthesis" |
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- "evaluation" |
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- "decision-making" |
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- "judgment" |
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- "insight" |
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- source_model: Qwen/Qwen1.5-0.5B |
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positive_prompts: |
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- "program" |
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- "software" |
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- "develop" |
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- "build" |
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- "create" |
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- "design" |
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- "implement" |
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- "debug" |
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- "test" |
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- "code" |
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- "python" |
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- "programming" |
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- "algorithm" |
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- "function" |
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- source_model: Qwen/Qwen1.5-0.5B |
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positive_prompts: |
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- "storytelling" |
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- "narrative" |
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- "fiction" |
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- "creative writing" |
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- "plot" |
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- "characters" |
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- "dialogue" |
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- "setting" |
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- "emotion" |
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- "imagination" |
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- "scene" |
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- "story" |
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- "character" |
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- source_model: Qwen/Qwen1.5-0.5B |
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positive_prompts: |
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- "chat" |
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- "conversation" |
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- "dialogue" |
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- "discuss" |
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- "ask questions" |
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- "share thoughts" |
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- "explore ideas" |
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- "learn new things" |
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- "personal assistant" |
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- "friendly helper" |
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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 |
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import transformers |
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import torch |
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model = "Isotonic/TinyQwex-4x620M-MoE" |
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tokenizer = AutoTokenizer.from_pretrained(model) |
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pipeline = transformers.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 = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True) |
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outputs = pipeline(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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``` |
