huihui-ai/gemma-3-27b-it-abliterated
The huihui-ai/gemma-3-27b-it-abliterated model is a 27 billion parameter instruction-tuned Gemma-3 variant developed by huihui-ai, featuring a 32K context length. This model has undergone an "abliteration" process to remove refusal behaviors, specifically targeting the removal of "I'm sorry, but I cannot fulfill your request" type responses. It is designed for use cases requiring an uncensored large language model, particularly for text-based interactions, and retains multimodal capabilities for image understanding.
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Hugging Face 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.
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frequency_penalty
This setting penalizes new tokens based on their frequency in the generated text. Values > 0 encourage new tokens; < 0 encourages repetition.
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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.
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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.