metadata
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
- [https://ko-fi.com/nexusnetworkint](Official Ko-FI link!)
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!