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EtherealAurora-12BYamatazen
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12B Params FP8 Open Weights Inference Available

EtherealAurora-12B by yamatazen is a ChatML-compatible language model created through a merge of several pre-trained models using the Model Stock method. It leverages yamatazen/Aurora-SCE-12B as its base, integrating yamatazen/Ayla-Light-12B-Stock, yamatazen/EtherealLight-12B, and yamatazen/Aurora-SCE-12B-v2. This model is designed for general chat applications, combining the strengths of its constituent models for diverse conversational capabilities.

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Parameters:12BContext length:32kArchitecture:TransformerPrecision:FP8Quantized variants:AvailableLast updated:March 2025
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yamatazen/EtherealAurora-12B
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.

1.25

top_p

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

0.7

top_k

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

60

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.

1.1

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.

0.1