huihui-ai/DeepSeek-R1-Distill-Qwen-32B-abliterated is a 32.8 billion parameter language model, derived from deepseek-ai/DeepSeek-R1-Distill-Qwen-32B. This model has been modified using an 'abliteration' technique to specifically remove refusal behaviors, making it an uncensored version. It serves as a proof-of-concept for removing LLM refusals without TransformerLens, primarily aimed at use cases requiring direct, unfiltered responses.
Loading preview...
Model tree for
huihui-ai/DeepSeek-R1-Distill-Qwen-32B-abliteratedMost 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.