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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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- DopeorNope/SOLARC-M-10.7B |
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- maywell/PiVoT-10.7B-Mistral-v0.2-RP |
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- kyujinpy/Sakura-SOLAR-Instruct |
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- jeonsworld/CarbonVillain-en-10.7B-v1 |
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--- |
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![image/png](https://cdn-uploads.huggingface.co/production/uploads/64545af5ec40bbbd01242ca6/Qb88YeudOf7MYuGKTirXC.png) |
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# Lumosia-MoE-4x10.7 |
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"Lumosia" was selected as its a MoE of Multiple SOLAR Merges so it really "Lights the way".... its 3am. |
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This is a very experimantal model. its a MoE of all good performing Solar models (based off of personal experiance not open leaderboard), |
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Why? Dunno whated to see what would happen |
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context is maybe 16k? waiting for GGUF to upload. |
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Chat-instruct breaks the model at the moment, not really sure why, even tho it will follow instructions. |
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Template: |
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``` |
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### System: |
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### USER:{prompt} |
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### Assistant: |
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``` |
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Settings: |
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``` |
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Temp: 1.0 |
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min-p: 0.02-0.1 |
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``` |
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Lumosia-MoE-4x10.7 is a Mixure of Experts (MoE) made with the following models: |
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* [DopeorNope/SOLARC-M-10.7B](https://huggingface.co/DopeorNope/SOLARC-M-10.7B) |
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* [maywell/PiVoT-10.7B-Mistral-v0.2-RP](https://huggingface.co/maywell/PiVoT-10.7B-Mistral-v0.2-RP) |
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* [kyujinpy/Sakura-SOLAR-Instruct](https://huggingface.co/kyujinpy/Sakura-SOLAR-Instruct) |
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* [jeonsworld/CarbonVillain-en-10.7B-v1](https://huggingface.co/jeonsworld/CarbonVillain-en-10.7B-v1) |
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## Evals: |
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* Pending |
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## Examples: |
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``` |
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Example 1: |
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User: |
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Hello lumi, what is the meaning of life |
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in around 100 words. |
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Lumosia: |
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The meaning of life can vary greatly |
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depending on individual beliefs, |
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values, and experiences. One common |
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perspective suggests that the primary |
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purpose of life is to seek happiness, |
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fulfillment, and personal growth |
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through relationships |
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accomplishments, and spiritual |
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awareness. Living with integrity. |
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compassion, and gratitude while |
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making a positive impact on others |
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and the world around us can also |
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contribute to finding meaning in life |
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UItimately, the meaning of life is |
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subjective and unique to each |
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individual, who must define it for |
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themselves through exploration |
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reflection, and personal choice. |
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``` |
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``` |
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Example 2: |
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User: |
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Explain a MoE (Mixture of Experts) in |
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around 100 words |
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Lumosia: |
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A MoE, short for Mixture of Experts, is |
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a machine learning technique utilized |
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in ensemble learning. It involves |
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combining multiple specialist models |
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(experts) to optimize predictive |
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performance. Each expert focuses on |
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a subset of the input features or data |
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domains, making them specialized in |
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particular areas. Through a weighting |
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mechanism, like Gaussian Mixture |
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Model, the predictions of experts are |
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blended to produce a final result. MoE |
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models demonstrate effectiveness in |
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handling complex or ambiguous |
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inputs where a single model might |
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struggle. They are commonly used in |
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natural language processing. |
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computer vision, and speech synthesis. |
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``` |
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## 🧩 Configuration |
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``` |
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yamlbase_model: DopeorNope/SOLARC-M-10.7B |
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gate_mode: hidden |
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dtype: bfloat16 |
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experts: |
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- source_model: DopeorNope/SOLARC-M-10.7B |
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positive_prompts: [""] |
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- source_model: maywell/PiVoT-10.7B-Mistral-v0.2-RP |
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positive_prompts: [""] |
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- source_model: kyujinpy/Sakura-SOLAR-Instruct |
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positive_prompts: [""] |
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- source_model: jeonsworld/CarbonVillain-en-10.7B-v1 |
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positive_prompts: [""] |
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``` |
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## 💻 Usage |
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``` |
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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/Lumosia-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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``` |