--- 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)