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@@ -50,18 +50,52 @@ metrics:
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  - **Dataset Combined Using:** Mosher-R1(Propietary Software)
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  - MiniMaid-L1 Official Metric Score
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- ![image/png](https://cdn-uploads.huggingface.co/production/uploads/6633a73004501e16e7896b86/194HxA6P0846242q7u_Y0.png)
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  - Metrics Made By **ItsMeDevRoland**
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  Which compares:
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  - **Deepseek R1 3B GGUF**
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  - **Dolphin 3B GGUF**
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  - **Hermes 3b Llama GGUFF**
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- - **OpenElla3-Llama3.2B GGUFF**
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  Which are All Ranked with the Same Prompt, Same Temperature, Same Hardware(Google Colab),
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  To Properly Showcase the differences and strength of the Models
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- - **THIS MODEL EXCELLS IN LONGER PROMPT AND STAYING IN CHARACTER BUT LAGS BEHIND DEEPSEEK-R1**
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  - # Notice
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  - **For a Good Experience, Please use**
@@ -78,4 +112,4 @@ metrics:
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  - This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
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  [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
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  - Fine-tuned Using:
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- - Google Colab
 
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  - **Dataset Combined Using:** Mosher-R1(Propietary Software)
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  - MiniMaid-L1 Official Metric Score
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+ ![image/png](https://cdn-uploads.huggingface.co/production/uploads/6633a73004501e16e7896b86/139GT5lXIeZKh3jccFFlG.png)
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  - Metrics Made By **ItsMeDevRoland**
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  Which compares:
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  - **Deepseek R1 3B GGUF**
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  - **Dolphin 3B GGUF**
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  - **Hermes 3b Llama GGUFF**
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+ - **MiniMaid-L1 GGUFF**
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  Which are All Ranked with the Same Prompt, Same Temperature, Same Hardware(Google Colab),
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  To Properly Showcase the differences and strength of the Models
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+ - **Visit Below to See details!**
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+
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+ ---
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+
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+ ## 🧵 MiniMaid-L1: A 1B Roleplay Assistant That Punches Above Its Weight
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+
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+ > She’s not perfect — but she’s fast, compact, and learning quick. And most importantly, **she didn’t suck**.
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+
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+ Despite her size, MiniMaid-L1 held her own against 3B models like **DeepSeek**, **Dolphin**, and **Hermes**.
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+ ![image/png](https://cdn-uploads.huggingface.co/production/uploads/6633a73004501e16e7896b86/VA2tYXbuU7yidiBl-osi_.png)
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+ 💬 **Roleplay Evaluation (v0)**
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+ - 🧠 Character Consistency: 0.50
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+ - 🌊 Immersion: 0.13
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+ - 🧮 Overall RP Score: 0.51
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+ - ✏️ Length Score: 0.91
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+
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+ - Even with only 1.5K synthetic samples, MiniMaid showed strong prompt structure, consistency, and resilience.
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+ ---
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+ ![image/png](https://cdn-uploads.huggingface.co/production/uploads/6633a73004501e16e7896b86/9JgGIvJ-yshztSuEFeuJs.png)
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+ 📊 **Efficiency Wins**
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+ - **Inference Time:** 49.1s (vs Hermes: 140.6s)
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+ - **Tokens/sec:** 7.15 (vs Dolphin: 3.88)
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+ - **BLEU/ROUGE-L:** Outperformed DeepSeek + Hermes
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+
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+ - MiniMaid proved that **you don’t need 3 billion parameters to be useful** — just smart distillation and a little love.
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+ ---
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+ 🛠️ **MiniMaid is Built For**
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+ - Lightweight RP generation
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+ - Low-resource hardware
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+ - High customization potential
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+
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+ 🌱 **She’s just getting started** — v1 is on the way with more character conditioning, dialogue tuning, and narrative personality control.
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+
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+ ---
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+ > “She’s scrappy, she’s stubborn, and she’s still learning. But MiniMaid-L1 proves that smart distillation and a tiny budget can go a long way — and she’s only going to get better from here.”
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+ ---
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  - # Notice
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  - **For a Good Experience, Please use**
 
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  - This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
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  [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
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  - Fine-tuned Using:
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+ - Google Colab