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bernie0.1Ivoras
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3.2B Params BF16 Open Weights Inference Available

ivoras/bernie0.1 is a 3.2 billion parameter proof-of-concept language model trained on the works of US Senator Bernie Sanders, featuring a 32768-token context length. Developed by ivoras, this model is an experimental "mind state" designed to respond as the original person would, focusing on topics related to Sanders' political views. It is specifically optimized for generating text and engaging in conversations reflecting the senator's perspectives on social and economic issues.

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Parameters:3.2BContext length:32kArchitecture:TransformerPrecision:BF16Quantized variants:AvailableLast updated:July 2025
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ivoras/bernie0.1
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.

top_p

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

top_k

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

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.

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.