huihui-ai/Huihui-Qwen3-0.6B-abliterated-v2

The huihui-ai/Huihui-Qwen3-0.6B-abliterated-v2 is an 0.8 billion parameter causal language model based on the Qwen3 architecture, developed by huihui-ai. This model is specifically designed as an uncensored version of Qwen/Qwen3-0.6B, created using an 'abliteration' method to remove refusal behaviors. It is optimized for research and experimental use cases where reduced safety filtering is desired, offering a proof-of-concept for uncensored LLM deployment.

Cold
Public
0.8B
BF16
40960
License: apache-2.0
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.
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.