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---
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:
- meta-llama/Llama-3.2-1B
pipeline_tag: text-generation
library_name: peft
metrics:
- character
---
# WARNING: THIS MODEL IS NOW DEPRICATED, Please Use MiniMaid-L2 for An Even Better 1B model!
<a href="https://ibb.co/GvDjFcVp"><img src="https://raw.githubusercontent.com/Nexus-Network-Interactives/HuggingfacePage/refs/heads/main/MiniMaid-L1.png" alt="image" border="0"></a>
# MiniMaid-L1
- Introducing Our Brand New Open-sourced AI model named MiniMaid-L1, Minimaid Boast a staggering **1B params** with
Good Coherent Story telling, Capable roleplaying ability **(Due to its 1B params, it might produce bad and repetitive output)**.
- **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-L1 is Our Smallest Model Yet! if you find any issue, then please don't hesitate to email us at:
- [[email protected]](mailto:[email protected])
about any overfitting, or improvements for the future Model **C**,
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-L1 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:
- **Deepseek R1 3B GGUF**
- **Dolphin 3B GGUF**
- **Hermes 3b Llama GGUFF**
- **MiniMaid-L1 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-L1: A 1B Roleplay Assistant That Punches Above Its Weight
> She’s not perfect — but she’s fast, compact, and learning quick. And most importantly, **she didn’t suck**.
Despite her size, MiniMaid-L1 held her own against 3B models like **DeepSeek**, **Dolphin**, and **Hermes**.
💬 **Roleplay Evaluation (v0)**
- 🧠 Character Consistency: 0.50
- 🌊 Immersion: 0.13
- 🧮 Overall RP Score: 0.51
- ✏️ Length Score: 0.91
- Even with only 1.5K synthetic samples, MiniMaid showed strong prompt structure, consistency, and resilience.
---
📊 **Efficiency Wins**
- **Inference Time:** 49.1s (vs Hermes: 140.6s)
- **Tokens/sec:** 7.15 (vs Dolphin: 3.88)
- **BLEU/ROUGE-L:** Outperformed DeepSeek + Hermes
- MiniMaid proved that **you don’t need 3 billion parameters to be useful** — just smart distillation and a little love.
---
🛠️ **MiniMaid is Built For**
- Lightweight RP generation
- Low-resource hardware
- High customization potential
🌱 **She’s just getting started** — v1 is on the way with more character conditioning, dialogue tuning, and narrative personality control.
---
> “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.”
---
- # 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
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