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GGUF-Imatrix quantizations for SanjiWatsuki/Kunoichi-DPO-v2-7B.

What does "Imatrix" mean?

It stands for Importance Matrix, a technique used to improve the quality of quantized models.

The Imatrix is calculated based on calibration data, and it helps determine the importance of different model activations during the quantization process. The idea is to preserve the most important information during quantization, which can help reduce the loss of model performance.

One of the benefits of using an Imatrix is that it can lead to better model performance, especially when the calibration data is diverse.

More information: [1] [2]

If you want any specific quantization to be added, feel free to ask.

All credits belong to the creator.

Base⇢ GGUF(F16)⇢ Imatrix-Data(F16)⇢ GGUF(Imatrix-Quants)

Using llama.cpp-b2277.

For --imatrix data, imatrix-Kunoichi-DPO-v2-7B-F16.dat was used.

Waifu card:

image/png

Original model information:

Model MT Bench EQ Bench MMLU Logic Test
GPT-4-Turbo 9.32 - - -
GPT-4 8.99 62.52 86.4 0.86
Kunoichi-DPO-v2-7B 8.51 42.18 64.94 0.58
Mixtral-8x7B-Instruct 8.30 44.81 70.6 0.75
Kunoichi-DPO-7B 8.29 41.60 64.83 0.59
Kunoichi-7B 8.14 44.32 64.9 0.58
Starling-7B 8.09 - 63.9 0.51
Claude-2 8.06 52.14 78.5 -
Silicon-Maid-7B 7.96 40.44 64.7 0.54
Loyal-Macaroni-Maid-7B 7.95 38.66 64.9 0.57
GPT-3.5-Turbo 7.94 50.28 70 0.57
Claude-1 7.9 - 77 -
Openchat-3.5 7.81 37.08 64.3 0.39
Dolphin-2.6-DPO 7.74 42.88 61.9 0.53
Zephyr-7B-beta 7.34 38.71 61.4 0.30
Llama-2-70b-chat-hf 6.86 51.56 63 -
Neural-chat-7b-v3-1 6.84 43.61 62.4 0.30
Model Average AGIEval GPT4All TruthfulQA Bigbench
Kunoichi-DPO-7B 58.4 45.08 74 66.99 47.52
Kunoichi-DPO-v2-7B 58.31 44.85 75.05 65.69 47.65
Kunoichi-7B 57.54 44.99 74.86 63.72 46.58
OpenPipe/mistral-ft-optimized-1218 56.85 44.74 75.6 59.89 47.17
Silicon-Maid-7B 56.45 44.74 74.26 61.5 45.32
mlabonne/NeuralHermes-2.5-Mistral-7B 53.51 43.67 73.24 55.37 41.76
teknium/OpenHermes-2.5-Mistral-7B 52.42 42.75 72.99 52.99 40.94
openchat/openchat_3.5 51.34 42.67 72.92 47.27 42.51
berkeley-nest/Starling-LM-7B-alpha 51.16 42.06 72.72 47.33 42.53
HuggingFaceH4/zephyr-7b-beta 50.99 37.33 71.83 55.1 39.7
Model AlpacaEval2 Length
GPT-4 23.58% 1365
GPT-4 0314 22.07% 1371
Mistral Medium 21.86% 1500
Mixtral 8x7B v0.1 18.26% 1465
Kunoichi-DPO-v2 17.19% 1785
Claude 2 17.19% 1069
Claude 16.99% 1082
Gemini Pro 16.85% 1315
GPT-4 0613 15.76% 1140
Claude 2.1 15.73% 1096
Mistral 7B v0.2 14.72% 1676
GPT 3.5 Turbo 0613 14.13% 1328
LLaMA2 Chat 70B 13.87% 1790
LMCocktail-10.7B-v1 13.15% 1203
WizardLM 13B V1.1 11.23% 1525
Zephyr 7B Beta 10.99% 1444
OpenHermes-2.5-Mistral (7B) 10.34% 1107
GPT 3.5 Turbo 0301 9.62% 827
Kunoichi-7B 9.38% 1492
GPT 3.5 Turbo 1106 9.18% 796
GPT-3.5 8.56% 1018
Phi-2 DPO 7.76% 1687
LLaMA2 Chat 13B 7.70% 1513
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GGUF
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