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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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- kodonho/SolarM-SakuraSolar-SLERP |
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- Sao10K/Sensualize-Solar-10.7B |
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- NousResearch/Nous-Hermes-2-SOLAR-10.7B |
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- fblgit/UNA-SOLAR-10.7B-Instruct-v1.0 |
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--- |
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# Umbra-MoE-4x10.7 |
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Umbra-MoE-4x10.7 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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* [kodonho/SolarM-SakuraSolar-SLERP](https://huggingface.co/kodonho/SolarM-SakuraSolar-SLERP) |
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* [Sao10K/Sensualize-Solar-10.7B](https://huggingface.co/Sao10K/Sensualize-Solar-10.7B) |
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* [NousResearch/Nous-Hermes-2-SOLAR-10.7B](https://huggingface.co/NousResearch/Nous-Hermes-2-SOLAR-10.7B) |
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* [fblgit/UNA-SOLAR-10.7B-Instruct-v1.0](https://huggingface.co/fblgit/UNA-SOLAR-10.7B-Instruct-v1.0) |
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## 🧩 Configuration |
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```yamlbase_model: kodonho/SolarM-SakuraSolar-SLERP |
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gate_mode: hidden |
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dtype: bfloat16 |
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experts: |
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- source_model: kodonho/SolarM-SakuraSolar-SLERP |
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positive_prompts: |
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- "versatile" |
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- "helpful" |
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- "factual" |
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- "integrated" |
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- "adaptive" |
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- "comprehensive" |
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- "balanced" |
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negative_prompts: |
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- "specialized" |
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- "narrow" |
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- "focused" |
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- "limited" |
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- "specific" |
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- source_model: Sao10K/Sensualize-Solar-10.7B |
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positive_prompts: |
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- "creative" |
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- "chat" |
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- "discuss" |
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- "culture" |
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- "world" |
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- "expressive" |
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- "detailed" |
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- "imaginative" |
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- "engaging" |
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negative_prompts: |
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- "sorry" |
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- "cannot" |
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- "factual" |
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- "concise" |
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- "straightforward" |
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- "objective" |
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- "dry" |
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- source_model: NousResearch/Nous-Hermes-2-SOLAR-10.7B |
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positive_prompts: |
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- "analytical" |
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- "accurate" |
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- "logical" |
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- "knowledgeable" |
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- "precise" |
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- "calculate" |
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- "compute" |
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- "solve" |
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- "work" |
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- "python" |
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- "javascript" |
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- "programming" |
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- "algorithm" |
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- "tell me" |
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- "assistant" |
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negative_prompts: |
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- "creative" |
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- "abstract" |
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- "imaginative" |
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- "artistic" |
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- "emotional" |
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- "mistake" |
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- "inaccurate" |
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- source_model: fblgit/UNA-SOLAR-10.7B-Instruct-v1.0 |
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positive_prompts: |
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- "instructive" |
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- "clear" |
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- "directive" |
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- "helpful" |
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- "informative" |
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negative_prompts: |
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- "exploratory" |
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- "open-ended" |
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- "narrative" |
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- "speculative" |
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- "artistic" |
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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 = "Steelskull/Umbra-MoE-4x10.7" |
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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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``` |
