Update README.md

README.md

@@ -1,22 +1,49 @@
 ---
-base_model: unsloth/llama-3.2-1b-instruct-unsloth-bnb-4bit
+license: apache-2.0
 tags:
+- unsloth
+- Uncensored
 - text-generation-inference
 - transformers
 - unsloth
 - llama
-- gguf
-license: apache-2.0
+- 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-L2
+pipeline_tag: text-generation
+library_name: peft
+metrics:
+- character
 ---
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/6633a73004501e16e7896b86/nQ1ZaTkikZLPfg8VTWnXL.png)
+# GGUF Version
+  **GGUF** with Quants! Allowing you to run models using KoboldCPP and other AI Environments!
 
-# Uploaded  model
-
-- **Developed by:** N-Bot-Int
-- **License:** apache-2.0
-- **Finetuned from model :** unsloth/llama-3.2-1b-instruct-unsloth-bnb-4bit
 
-This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
+# Quantizations:
+| Quant Type    | Benefits                                          | Cons                                              |
+|---------------|---------------------------------------------------|---------------------------------------------------|
+| **Q4_K_M**    | ✅ Smallest size (fastest inference)              | ❌ Lowest accuracy compared to other quants      |
+|               | ✅ Requires the least VRAM/RAM                    | ❌ May struggle with complex reasoning           |
+|               | ✅ Ideal for edge devices & low-resource setups   | ❌ Can produce slightly degraded text quality    |
+| **Q5_K_M**    | ✅ Better accuracy than Q4, while still compact   | ❌ Slightly larger model size than Q4            |
+|               | ✅ Good balance between speed and precision       | ❌ Needs a bit more VRAM than Q4                 |
+|               | ✅ Works well on mid-range GPUs                   | ❌ Still not as accurate as higher-bit models    |
+| **Q8_0**      | ✅ Highest accuracy (closest to full model)       | ❌ Requires significantly more VRAM/RAM          |
+|               | ✅ Best for complex reasoning & detailed outputs  | ❌ Slower inference compared to Q4 & Q5          |
+|               | ✅ Suitable for high-end GPUs & serious workloads | ❌ Larger file size (takes more storage)         |
 
-[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
+# Model Details:
+  Read the Model details on huggingface
+  [Model Detail Here!](https://huggingface.co/N-Bot-Int/MiniMaid-L2)