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# Lumosia-v2-MoE-4x10.7 |
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The Lumosia Series upgraded with Lumosia V2. |
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# What's New in Lumosia V2? |
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Lumosia V2 takes the original vision of being an "all-rounder" and refines it with more nuanced capabilities. |
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Topic/Prompt Based Approach: |
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Diverging from the keyword-based approach of its counterpart, Umbra. |
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Context and Coherence: |
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With a base context of 8k scrolling window and the ability to maintain coherence up to 16k. |
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Balanced and Versatile: |
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The core ethos of Lumosia V2 is balance. It's designed to be your go-to assistant. |
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Experimentation and User-Centric Development: |
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Lumosia V2 remains an experimental model, a mosaic of the best-performing Solar models, (selected based on user experience). |
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This version is a testament to the idea that innovation is a journey, not a destination. |
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Come join the Discord: |
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[ConvexAI](https://discord.gg/yYqmNmg7Wj) |
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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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## Evals: |
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* Avg: |
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* ARC: |
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* HellaSwag: |
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* MMLU: |
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* T-QA: |
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* Winogrande: |
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* GSM8K: |
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## Examples: |
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``` |
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Example 1: |
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User: |
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Lumosia: |
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``` |
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``` |
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Example 2: |
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User: |
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Lumosia: |
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``` |
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## 🧩 Configuration |
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``` |
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yaml |
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base_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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``` |