amoral-gemma3-12B-v2Soob3123
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12B Params FP8 Inference Available

The soob3123/amoral-gemma3-12B-v2 is a 12 billion parameter language model based on the Gemma 3 architecture, designed to provide analytically neutral responses to sensitive and controversial queries. It focuses on maintaining factual integrity and avoiding value judgments or emotional framing in its outputs. This model is optimized for use cases requiring objective information delivery without inherent moral biases.

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Parameters:12BContext length:32kArchitecture:TransformerPrecision:FP8Quantized variants:AvailableLast updated:March 2025
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soob3123/amoral-gemma3-12B-v2
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.

0.69

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.

-1

frequency_penalty

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

0.04

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.

0.04

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.

1.1

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.