MiniMaid-L2

• MiniMaid-L2 is a Finetuned Model of MiniMaid-L1 model, with even big and higher quality dataset used to generated roleplaying Capabilities, MiniMaid-L2 also were extracted from Knowledge Distilling A Popular Roleplaying Model named NoroMaid-7B-DPO, Which we've used to enchanced its lacking Ends for coherent And Good Roleplaying Capabilities.

• MiniMaid-L2 Outcompete its predecessor as it uses a Clever Knowledge distilling to transfer Knowledge from NoroMaid, And Finetuned it, building on top of MiniMaid-L1 to Produce a better AI model. Sacrificing Some Non-noticable Token-Generation speed, with a near perfect and Competitive Model against 3b Alternatives!

MiniMaid-L1 Base-Model Card Procedure:

• MiniMaid-L1 achieve a good Performance through process of DPO and Combined Heavy Finetuning, To Prevent Overfitting, We used high LR decays, And Introduced Randomization techniques to prevent the AI from learning and memorizing, However since training this on Google Colab is difficult, the Model might underperform or underfit on specific tasks Or overfit on knowledge it manage to latched on! However please be guided that we did our best, and it will improve as we move onwards!

• MiniMaid-L2 is Another Instance of Our Smallest Model Yet! if you find any issue, then please don't hesitate to email us at: [email protected] about any overfitting, or improvements for the future Model V3, Once again feel free to Modify the LORA to your likings, However please consider Adding this Page for credits and if you'll increase its Dataset, then please handle it with care and ethical considerations

• MiniMaid-L2 is

  • Developed by: N-Bot-Int
  • License: apache-2.0
  • Parent Model from model: unsloth/llama-3.2-3b-instruct-unsloth-bnb-1bit
  • Dataset Combined Using: Mosher-R1(Propietary Software)

• MiniMaid-L1 Official Metric Score

  • Metrics Made By ItsMeDevRoland Which compares:

    • MiniMaid-L1 GGUFF
    • MiniMaid-L2 GGUFF Which are All Ranked with the Same Prompt, Same Temperature, Same Hardware(Google Colab), To Properly Showcase the differences and strength of the Models

  • Visit Below to See details!

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🧵 MiniMaid-L2: Small Size, Big Bite — The Next-Gen Roleplay Assistant

She’s sharper, deeper, and more immersive. And this time? She doesn’t just hold her own — she wins.

MiniMaid-L2 builds on the scrappy L1 foundation and takes the lead over 3B giants like Hermes, Dolphin, and DeepSeek, with better consistency, longer outputs, and a massive boost to immersion.

• 💬 Roleplay Evaluation (v1)
• 🧠 Character Consistency: 0.84
• 🌊 Immersion: 0.47 -🧮 Overall RP Score: 0.76
• ✏️ Length Score: 1.00
• L2 scored +0.25 higher overall than L1, while beating top-tier 3B models in every major RP metric.

📊 Efficient AND Smart

• Inference Time: 54.2s — still 3x faster than Hermes
• Tokens/sec: 6.88 — near-instant on consumer GPUs
• BLEU/ROUGE-L: Stronger n-gram overlap than any 3B rival

MiniMaid-L2 shows that distilled models can outperform much larger ones — when trained right, even 1B can be the boss.

• 🛠️ MiniMaid is Built For
• High-fidelity RP generation
• Lower-latency systems
• Custom, character-driven storytelling

🌱 L2 is the turning point — with upgraded conditioning, tighter personality anchoring, and narrative-aware outputs, she's evolving fast.

“MiniMaid-L2 doesn’t just punch above her weight — she’s taking belts. A tighter model, a stronger performer, and still tiny enough to run on a toaster. RP just got smarter.”

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• Notice

  • For a Good Experience, Please use
    • Low temperature 1.5, min_p = 0.1 and max_new_tokens = 128

• Detail card:

  • Parameter

    • 1 Billion Parameters
    • (Please visit your GPU Vendor if you can Run 1B models)

  • Finetuning tool:

  • Unsloth AI

    • This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.

  • Fine-tuned Using:

  • Google Colab