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Cydonia-v4-MS3.2-Magnum-Diamond-24BKnifeayumu
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24B Params FP8 Open Weights Inference Available

Cydonia-v4-MS3.2-Magnum-Diamond-24B is a 24 billion parameter language model developed by knifeayumu, created through a SLERP merge of TheDrummer/Cydonia-24B-v4 and Doctor-Shotgun/MS3.2-24B-Magnum-Diamond. This model aims to refine the behavior of its constituents, specifically addressing verbosity and 'horniness' observed in MS3.2-24B-Magnum-Diamond. It is designed for general language generation tasks, offering a balanced output by combining characteristics of its merged components.

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Parameters:24BContext length:32kArchitecture:TransformerPrecision:FP8Quantized variants:AvailableLast updated:July 2025
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knifeayumu/Cydonia-v4-MS3.2-Magnum-Diamond-24B
Popular Sampler Settings

Most commonly used values from Featherless users

temperature

This setting influences the sampling randomness. Lower values make the model more deterministic; higher values introduce randomness. Zero is greedy sampling.

0.82

top_p

This setting controls the cumulative probability of considered top tokens. Must be in (0, 1]. Set to 1 to consider all tokens.

0.95

top_k

This limits the number of top tokens to consider. Set to -1 to consider all tokens.

26

frequency_penalty

This setting penalizes new tokens based on their frequency in the generated text. Values > 0 encourage new tokens; < 0 encourages repetition.

–

presence_penalty

This setting penalizes new tokens based on their presence in the generated text so far. Values > 0 encourage new tokens; < 0 encourages repetition.

–

repetition_penalty

This setting penalizes new tokens based on their appearance in the prompt and generated text. Values > 1 encourage new tokens; < 1 encourages repetition.

1

min_p

This setting representing the minimum probability for a token to be considered relative to the most likely token. Must be in [0, 1]. Set to 0 to disable.

0.05