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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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- macadeliccc/Samantha-Qwen2-1.5B |
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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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- macadeliccc/Samantha-Qwen2-1.5B |
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--- |
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# Qwen2-2x1.5B |
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Qwen2-2x1.5B 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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* [macadeliccc/Samantha-Qwen2-1.5B](https://huggingface.co/macadeliccc/Samantha-Qwen2-1.5B) |
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## 🧩 Configuration |
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```yaml |
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base_model: cognitivecomputations/dolphin-2.9.3-qwen2-1.5b |
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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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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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- "chat" |
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- "assistant" |
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- "explain" |
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- "describe" |
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- "define" |
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- "what is" |
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- "tell me" |
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- "help me" |
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- "show me" |
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- "can you" |
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- source_model: macadeliccc/Samantha-Qwen2-1.5B |
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positive_prompts: |
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- "characters" |
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- "scene" |
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- "roleplay" |
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- "writing" |
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- "creative" |
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- "you are" |
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- "act as" |
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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: # required by Qwen MoE for "hidden" gate mode, otherwise not allowed |
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- "chat" |
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- "assistant" |
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# (optional, but recommended:) |
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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 |
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import transformers |
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import torch |
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model = "djuna/Qwen2-2x1.5B" |
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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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``` |
