| | --- |
| | license: apache-2.0 |
| | tags: |
| | - unsloth |
| | - Uncensored |
| | - text-generation-inference |
| | - transformers |
| | - unsloth |
| | - llama |
| | - trl |
| | - roleplay |
| | - conversational |
| | datasets: |
| | - iamketan25/roleplay-instructions-dataset |
| | - N-Bot-Int/Iris-Uncensored-R1 |
| | - N-Bot-Int/Moshpit-Combined-R2-Uncensored |
| | - N-Bot-Int/Mushed-Dataset-Uncensored |
| | - N-Bot-Int/Muncher-R1-Uncensored |
| | - N-Bot-Int/Millia-R1_DPO |
| | language: |
| | - en |
| | base_model: |
| | - N-Bot-Int/MiniMaid-L1 |
| | pipeline_tag: text-generation |
| | library_name: peft |
| | metrics: |
| | - character |
| | --- |
| |  |
| | # 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: |
| | [nexus.networkinteractives@gmail.com](mailto:nexus.networkinteractives@gmail.com) |
| | 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!** |
| |
|
| | --- |
| | # 🧵 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.” |
| |
|
| | --- |
| |
|
| | - # 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](https://github.com/unslothai/unsloth) and Huggingface's TRL library. |
| | [<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth) |
| | - Fine-tuned Using: |
| | - Google Colab |
