N-Bot-Int
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MiniMaid-L2

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 ---
-base_model: unsloth/llama-3.2-1b-instruct-unsloth-bnb-4bit
 library_name: peft
 ---
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-### Framework versions
-- PEFT 0.14.0

 ---
+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
 ---
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/6633a73004501e16e7896b86/_sz14A_VdUTrnLEE4T16Z.png)
+# 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
+    ![image/png](https://cdn-uploads.huggingface.co/production/uploads/6633a73004501e16e7896b86/OPewz6mds2jATHlveEe11.png)
+    - 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