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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
---
<a href="https://imgbb.com/"><img src="https://raw.githubusercontent.com/Nexus-Network-Interactives/HuggingfacePage/refs/heads/main/MistThena7BGGUF.webp" alt="1741962015516" border="0"></a>
# 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) |