InferenceIllusionist/magnum-12b-v2.5-kto-iMat-GGUF

<img src="https://i.imgur.com/P68dXux.png" width="400"/>

magnum-12b-v2.5-kto-iMat-GGUF

[!WARNING] <b>Important Note:</b> Inferencing in llama.cpp has now been merged in PR #8604. Please ensure you are on release b3438 or newer. Text-generation-web-ui (Ooba) is also working as of 7/23. Kobold.cpp working as of v1.71. </b>

Quantized from magnum-12b-v2.5-kto fp16

• —Weighted quantizations were creating using fp16 GGUF and groups_merged.txt (special thanks to Kalomaze) in 92 chunks and n_ctx=512
• —Static fp16 will also be included in repo
• —For a brief rundown of iMatrix quant performance please see this PR
• —<i>All quants are verified working prior to uploading to repo for your safety and convenience</i>

<b>KL-Divergence Reference Chart</b> (Click on image to view in full size) <img src="https://i.imgur.com/mV0nYdA.png" width="920"/>

[!TIP] <b>Quant-specific Tips:</b> If you are getting a `cudaMalloc failed: out of memory` error, try passing an argument for lower context in llama.cpp, e.g. for 8k: `-c 8192` If you have all ampere generation or newer cards, you can use flash attention like so: -fa * Provided Flash Attention is enabled you can also use quantized cache to save on VRAM e.g. for 8-bit: -ctk q8_0 -ctv q8_0

Original model card can be found here