README.md

---
base_model:
- N-Bot-Int/MistThena7B
tags:
- text-generation-inference
- transformers
- mistral
- rp
- gguf
language:
- en
license: apache-2.0
datasets:
- 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
- unalignment/toxic-dpo-v0.1
library_name: transformers
new_version: N-Bot-Int/MistThena7BV2-GGUF
---
# Support Us Through
  - [![ko-fi](https://ko-fi.com/img/githubbutton_sm.svg)](https://ko-fi.com/J3J61D8NHV)
  - [https://ko-fi.com/nexusnetworkint](Official Ko-FI link!)

![image/png](https://cdn-uploads.huggingface.co/production/uploads/6633a73004501e16e7896b86/s4NcmxJ2pyBpDeULdYayv.png)
# GGUF Version
  **GGUF** with Quants! Allowing you to run models using KoboldCPP and other AI Environments!


# 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)         |

# Model Details:
  Read the Model details on huggingface
  [Model Detail Here!](https://huggingface.co/N-Bot-Int/MistThena7B)