No, DeepSeek isn’t uncensored if you run it locally
No, DeepSeek isn’t uncensored if you run it locally
DeepSeek's model is censored at both the application and training layers, a Wired investigation shows.
There’s an idea floating around that DeepSeek’s well-documented censorship only exists at its application layer but goes away if you run it locally (that means downloading its AI model to your computer).
But DeepSeek’s censorship is baked-in, according to a Wired investigation which found that the model is censored on both the application and training levels.
For example, a locally run version of DeepSeek revealed to Wired thanks to its reasoning feature that it should “avoid mentioning” events like the Cultural Revolution and focus only on the “positive” aspects of the Chinese Communist Party.
A quick check by TechCrunch of a locally run version of DeepSeek available via Groq also showed clear censorship: DeepSeek happily answered a question about the Kent State shootings in the U.S., but replied “I cannot answer” when asked about what happened in Tiananmen Square in 1989.
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At least unlike “Open”AI, it’s open source so you can see and fix its biases.
Good luck determining which combination of its 1.5 billions weights/biases corresponds to sympathy for the chinese.
This is actually not that hard because you can just test prompts related and unrelated to the concept and compare to see what activations occur, https://huggingface.co/blog/mlabonne/abliteration the same process could apply to any concept
No, it's not open source. Only the model weights are open, the datasets and code used to train the model are not.
Pretty sure the code used to train the model is open source? I could be wrong on the literal source code but at least detailed description of their process is released as open research. There is a current effort to reproduce it: https://github.com/huggingface/open-r1
The guardrails can be removed though, and several models already do, so his point is correct, regardless
you cannot unstir an egg, the guardrails and biases can be finetuned to not be as visible, but the training is ultimately irreversible.